Volatility
Illuminated
by
Mark Whistler
Mark Whistler | Trader | Author.
Mark Whistler is primarily an independent full time trader.
Whistler has appeared on CNBC and is a regular contributor to
FXStreet.com, discussing currency trading and global markets.
From time to time, Whistler assists with content as a contributing
Senior Market Strategist to TradingMarkets.com.
His books include:
 Macro to Micro Volatility Trading (CreateSpace, 2010)
 Volatility Illuminated (CreateSpace, 2009)
 2034 The Corporation Post 2012 (CreateSpace, 2009)
 The Swing Trader's Bible (John Wiley & Sons, Inc., 2008)
 Trade With Passion and Purpose (Wiley, 2007)
 Trading Pairs (Wiley, 2004)
 Profit from China (Investment U/Wiley, 2006)
 Profit from Uranium (Investment U/Wiley, 2006)
Mark Whistler is also the founder of WallStreetRockStar.com, fxVolatility.com,
ForexMetaTraderRobot.com, iOnlineForexTrading.com, iForexFeed.com, and
iForexEA.com.
Whistler is also a regular columnist for Investopedia.com. In his spare time, Mr.
Whistler operates Eats For The Streets, a growing organization - dedicated to helping
homeless across America and the MarkWhistlerGallery.com , an unbiased Internet art
gallery open to all artists (globally) seeking to display their works.
Volatility Illuminated by Mark Whistler
Copyright © 2009 Mark Whistler - All rights reserved.
Media@ Wallstreetrockstar.com
www.fxVolatility.com.com | www.Wallstreetrockstar.com
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Limit of Liability/Disclaimer of Warranty: While the author has used his best efforts in
preparing this book, he makes no representations or warranties with respect to the
accuracy or completeness of the contents of this book and specifically disclaims any
implied warranties of merchantability or fitness for a particular purpose. No warranty
may be created or extended by sales representatives or written sales materials. The
information contained herein may not be suitable to be taken as empirical truth. You
should consult with a professional when and where appropriate. Neither the author,
the editor, nor the publisher shall be liable for any personal, or commercial damages,
including but not limited to special, incidental, consequential, or other damages.
Library of Congress Cataloging-in-Publication Data:
ISBN 1441490795 EAN-13 X 9781441490797
Printed in the United States of America, New York, New York
First Edition June 2009/First Printing June 2009
Limit of Liability / Disclaimer of
Warranty (EXTENDED)
PairsTrader.com, Inc. LLC, [WallStreetRockStar.com, FXVolatility.com and Mark
Whistler] ("Company") is not an investment advisory service, nor a registered
investment advisor or broker-dealer and does not purport to tell or suggest which
securities or currencies customers should buy or sell for themselves. The principals,
analysts and employees or affiliates of Company may hold positions in the stocks,
currencies, and/or industries discussed here.
You understand and acknowledge that there is a very high degree of risk
involved in trading securities and/or currencies.
The Company, the authors, the publisher, and all affiliates of Company assume no
responsibility or liability for your trading and investment results. Factual statements on
the Company's website, or in its publications, are made as of the date stated and are
subject to change without notice. It should not be assumed that the methods,
techniques, or indicators presented in these products will be profitable or that they will
not result in losses. Past results of any individual trader or trading system published by
Company are not indicative of future returns by that trader or system, and are not
indicative of future returns which be realized by you.
In addition, the indicators, strategies, columns, articles and all other features of
Company's products (collectively, the "Information") are provided for informational
and educational purposes only and should not be construed as investment advice.
Examples presented on Company's website are for educational purposes only. Such
setups are not solicitations of any order to buy or sell. Accordingly, you should not rely
solely on the Information in making any investment. Rather, you should use the
Information only as a starting point for doing additional independent research in order
to allow you to form your own opinion regarding investments. You should always
check with your licensed financial advisor and tax advisor to determine the suitability
of any investment.
HYPOTHETICAL OR SIMULATED PERFORMANCE RESULTS HAVE CERTAIN
INHERENT LIMITATIONS. UNLIKE AN ACTUAL PERFORMANCE RECORD,
SIMULATED RESULTS DO NOT REPRESENT ACTUAL TRADING AND MAY NOT
BE IMPACTED BY BROKERAGE AND OTHER SLIPPAGE FEES. ALSO, SINCE THE
TRADES HAVE NOT ACTUALLY BEEN EXECUTED, THE RESULTS MAY HAVE
UNDER- OR OVERCOMPENSATED FOR THE IMPACT, IF ANY, OF CERTAIN
MARKET FACTORS, SUCH AS LACK OF LIQUIDITY. SIMULATED TRADING
PROGRAMS IN GENERAL ARE ALSO SUBJECT TO THE FACT THAT THEY ARE
DESIGNED WITH THE BENEFIT OF HINDSIGHT. NO REPRESENTATION IS BEING
MADE THAT ANY ACCOUNT WILL OR IS LIKELY TO ACHIEVE PROFITS OR
LOSSES SIMILAR TO THOSE SHOWN.
ADDITIONAL NOTICE TO
FOREX/CURRENCY TRADERS
Trading foreign exchange on margin carries a high level of risk and may not
be suitable for all investors. The high degree of leverage can work against you as
well as for you. Before deciding to trade foreign exchange, you should carefully
consider your investment objectives, level of experience and risk appetite. The
possibility exists that you could sustain a loss of some or all of your initial
investment and therefore you should not invest money that you cannot afford to
lose. You should be aware of all the risks associated with foreign exchange
trading and seek advice from an independent financial advisor if you have any
doubts. ..
THE INFORMATION AND STRATEGIES IN THIS BOOK DO NOT MAKE ANY
PROMISE, OR GUARANTEE. MARKET CONDITIONS CONTINUALLY
CHANGE AND THUS, INFORMATION PROVIDED IN VOLATILITY
UNLIMITED COULD CHANGE AS WELL.
YOU SHOULD SEEK PROFESSIONAL ADVICE PROACTIVELY, DURING
AND AFTER ATTEMPTING TO IMPLEMENT ANY
STRATEGY/INFORMATION NEW TO YOU AND YOUR TRADING
KNOWLEDGE, OR STYLE.
NEARLY 95% OF ALL RETAIL TRADERS LOSE.
PLEASE DO NOT ATTEMPT TO TRADE FOREX IF YOU FEEL THE
AFOREMENTIONED EVEN REMOTELY APPROACHES YOUR RISK
TOLERANCE. THE BEST ADVICE TO MOST INDIVIDUAL'S CONSIDERING
TRADING FOREX – IS UNLESS YOU HAVE PROFESSIONAL HELP – DON'T.
ACKNOWLEDGEMENTS
Sandy and Ed – Thank you! I love you! Karen, Mike and brilliant Ryan! I love
you!
Thank you FxStreet…Maud and Vicki… Your patience is amazing!
Thank you Michael Soni for your time and guidance (and the initial 'poison tree'
metaphor.) I really appreciate all that you've done!
Thank you Alvin Yu, Adam Huo and all of ECTrader.Net in Guangzhou, China.
To Francois, thanks for still believing in me… We're almost there!
To Mark and Tanya Harrison… Mark I am very excited for your new book on
Mortgages to hit shelves soon! Mark, you're an incredible writer! Thank you Ed
Carson for your friendship, past guidance and continued support. Thank you to
TradingMarkets.com and to Investopedia.com - Chris! Thank you Carl Killough, your
trading is brilliant buddy – perhaps one of the best I know!
Thank you to everyone who I have not mentioned who stuck by me during the
composition of Volatility Illuminated… The project pushed every ounce of everything
I have to the brink… I cannot thank you enough for not giving up!
Thank you Marcel ter Beek for your feedback and patience! Last, but not least,
thank you Joe O'Connor for editing the first version of the probability article!
Table of Contents
LIMIT OF LIABILITY / DISCLAIMER OF WARRANTY (EXTENDED)
ADDITIONAL NOTICE TO FOREX/CURRENCY TRADERS
ACKNOWLEDGEMENTS
PART ONE PARADIGM AT SEA
CHAPTER ONE
WHY SUPERMAN WEARS HIS UNDERPANTS ON THE OUTSIDE
3
THE MAJORITY IS ALWAYS WRONG – ESPECIALLY RETAIL TRADERS
16
THE PRINCIPLE OF BUOYANCY IN MARKETS
19
CHAPTER TWO
WHY INDICATORS ARE FAILING IN THE CURRENT MARKET
26
RETAIL VERSUS INSTITUTION
27
LOCK, STOCK AND DOGMA
29
HIIV EFFECT IN ACTION
31
FINDING SANITY WITHIN THE CHAOS
33
CHAPTER THREE
BEHIND THE CURTAIN
36
THE PHILOSOPHY OF LOOKING BEHIND THE CURTAIN, EVEN IF IT'S NOT SOCIALLY APPROPRIATE
37
THE STORY OF BLACK MONDAY - 1987
41
THE CONFESSION OF MASS MEMORY FAILURE
45
A DATE WITH BLIND DEVOTION
48
MEDIA MADE MALADAPTIVE MEMORY
57
THE ACCEPTED STANDARD OF NOTHINGNESS
63
TO SEE VOLATILITY ILLUMINATED YOU MUST BE WILLING TO
67
SEE INFORMATION CLEARLY
67
CHAPTER FOUR
FIBONACCI & PITCHFORKS
71
FIBONACCI IN NATURE
72
THE FIBONACCI PROPHECY
73
FIBONACCI RETRACEMENT VOLATILITY
79
AS SIMPLE AS A PITCHFORK
81
MACRO TO MICRO PITCHFORKS
85
DAILY CHART IN ACTION
88
4-HOUR CHART
89
NOTE
93
CHAPTER FIVE
94
VOLATILITY ADJUSTED FOREX FIBONACCI PITCHFORK STRATEGY
94
RULES TO FOLLOW
102
A FEW FINAL NOTES
103
CHAPTER SIX
QUAD CCI – THE TRADITIONAL VOLATILITY PARADIGM
104
STANDARD STAN AND THE FOUR HORSEMEN
117
IDENTIFYING POTENTIAL REVERSALS WITH CCI
122
PART TWO VOLATILITY ILLUMINATED
CHAPTER SEVEN
INFORMATION ACCELERATION IN THE 21ST CENTURY AND THE VOLATILITY PARADIGM
128
PRE-LOADING MAJOR
130
MARKETS FOR VOLATILITY
130
MARKET VOLATILITY THROUGH EINSTEIN'S THEORY OF SPECIAL RELATIVITY
141
CRITICAL MASS AND CONSCIOUS UNAWARENESS
147
THE TIPPING POINT OF INFORMATION MASS
152
CHAPTER EIGHT
VOLATILITY AND PROBABILITY THROUGH THE MOVEMENT OF DISTRIBUTIONS
162
WORDS OF CAUTION
164
TRANSCENDING MARKETS THROUGH VOLATILITY AND PROBABILITY
165
GAUSSIAN CURVE REVISITED
170
THE EXPANSION AND COMPRESSION OF SUBSET DISTRIBUTIONS
183
CHAPTER NINE
VOLUME WEIGHTED AVERAGE PRICE (VWAP)
197
CHAPTER TEN
- WVAV -
209
WHISTLER VOLUME ADJUSTED VOLATILITY
209
WHAT IS WVAV?
210
MEASURING MASS AND ENERGY
211
MASS AND ENERGY THROUGH STANDARD DEVIATIONS
219
WHAT THE MULTIPLIER EFFECT MEANS TO US
221
WHY DO WE LOOK FOR VOLATILITY SPIKES?
222
WVAV VOLATILITY/ENERGY
225
CHAPTER ELEVEN
THE PHILOSOPHY OF ORDERFLOW AND MARKETS
234
MOST RETAIL TRADERS NEVER CONSIDER THE TERM 'BENCHMARK'
238
BIOVAP MAN AND THE INSANITY OF DR. WATERMELON STUFFER
242
BUY SIDE/SELL SIDE
243
CHAPTER TWELVE
WAVE • PM
251
WAVE • PM, WVAV AND QUAD CCI
258
CHAPTER THIRTEEN
THE DYNAMIC MOVEMENTS OF SUBSET DISTRIBUTIONS
262
THE NEVER-ENDING SEARCH BEHIND PROBABILITY DISTRIBUTIONS
263
CHINESE RESTAURANT PROCESS, PROBABILITY/ VOLATILITY AND DISTRIBUTIONS
266
PROBABILITY DENSITY
268
FUNCTION (PDF)
268
RULES OF TRADING DISAPLINE
272
SIX CORE PRINCIPLES OF TECHNICAL ANALYSIS
274
ADDITIONAL DISCLAIMER
275
CUSTOM INDICATOR CODE I
WAVE ● PM
276
CUSTOM INDICATOR CODE II
DUEL CCI WITH SIGNAL
280
CUSTOM INDICATOR CODE III
WVAV
284
BIBLIOGRAPHY / RECOMMENDED READING
288
END NOTES
289
PART ONE
PARADIGM AT SEA
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Chapter One
WHY SUPERMAN WEARS HIS
UNDERPANTS ON THE OUTSIDE
"Believe nothing, no matter where you read it, or
who said it, no matter if I have said it, unless it
agrees with your own reason and your own
common sense."
~ Hindu Prince Gautama Siddharta
J
ust possibly, a significant portion of the information we've been traditionally
taught to think of as 'accurate' in trading, investing and life, might be
flawed...especially what we perceive as the best possible order for our underpants.
I hate to say it, but it's true. After ten years of research, trading, analysis, writing six
books and over 1,500 articles about various aspects of markets, I am convinced the
mass public (and most of the experts) are snowed.
The present epidemic of misinformed masses is precisely why over the following
pages, I will present multiple cases showing how the majority's perception of
information and markets is drastically flawed.
In addition, while many believe 21st century technology has created a more
productive, 'progressive' and intelligent society, in reality (at least, as seen from the
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trading floor) the greater public seems to actually be regressing in ability to accurately
perceive major market moving events significantly beforehand.
Underlying causes are both complicated and numerous; however, our
contemporary light speed of information, increasingly 'factory setting' dependant
mindset and growing naive trust of 'fast-mass media' all stand out as bold culprits
behind humanity's swelling herd behavior.
On the outset, retail traders often complain of increased volatility in today's market,
seemingly from nowhere.
The retail trader is correct about one thing; volatility is becoming fiercer in markets,
especially Forex.
While we personally have zero ability to halt erratic market swings (a larger
archetype than we are, of course), we can attempt to see today's erratic Volatility
Illuminated through diligent, open-minded and perseverant investigation. To do so
though, we will need to find new flashlights capable of cutting through the thick fog,
which has now settled upon markets.
Unfortunately, in today's trading environment (even with all of our high-tech
everything) most retail traders, media pundits and even professionals simply cannot
see three feet beyond their nose, let alone light a reliable path into the distance.
Fact is, analysts, retail traders, media and even many high-finance professionals feel
empowered with their 50,000 watt technical analysis and 'reliable information' fog
lights.
We're really talking about the blind and oblivious mass acceptance of mucky, grimy,
tampered, booby trapped, credulous and opinionated information, simply because
such is 'the accepted standard'.
The problem is, the big shiny lights do nothing more than actually create a 'blinding
screen' on the face of the brume.
All too often, media, analysts, and masses don't even have a clue the tool they're
depending on for guidance, is really the problem.
Even if you are aware of the situation, don't bother attempting to mention the
problem; you'll just hear something like:
"It's commonly known this thing can light up a cliff 1,000 miles away. Besides, I'm
'certified' to use it; didn't you see my credentials in the capital letters after my last
name? And I wasn't trained to use the big light just anywhere; my school was ivy."
You might reply, "Don't you mean 1,000 miles, on a clear night?"
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"This bulb is the best money can buy...and I've got credentials," the financial
professional replies.
Just to be nice you offer, "I know the bulb is expensive, but I have an extra one here
in my pocket, it's specially designed for fog... You're welcome to borrow it."
The troop leader turns away with an abase chuckle- while rolling his eyes in the
vision of his witless 'mega-fog-light' followers.
You can't be angry though; you just feel bad for the whole group.
Sadly, the general public is attracted to the same media/analyst big light too, all
believing there's no way mainstream media and Wall Street professionals could be so
obtuse, as to not truly know what they're doing…and off into the night they march.
Making matters worse, brokers and financial news portals have generously
provided all customers with the exact same personal wide beam fog light contraptions for
use during their little expedition into the darkness.
Nevertheless, the identical wide beam spots only make the crowd more dim-sighted
by adding another layer of glare to the front side of the fog. Really, the mega-light
fanatics are creating a sort of floating (though radiant) sheeting only a few feet into
their speculated direction. Because the masses do, in fact, all have their own little lights
they think are worthwhile too, while the 50,000-watt media monkey's prod from
behind, they all start dashing into the fog…
Clueless of the cliff just a few feet away...
Over the following pages, I will attempt to provide a very, very special flashlight….
Not only does it perform well, but it works in rain, snow, fog and of course, on a clear
night.
Moreover, I think once you switch it on, you're going just stand there speechless and
shocked, as you begin to see the terrain (beyond the fog), for the first time, in a long
time.
You will also likely look over at the larger media/analyst/retail troop marching
credulously into the night…and say nothing.
You would normally laugh at the current situation, but you can't, it's devastating.
You're standing there with your light – you can see – and because you can, you
know the herd…the retail traders and investors, all with their identical broker issued
spots and the media with their analyst fueled 50,000-watt mega-mouth beams…are all
swaggering into the foggy night, totally clueless they're just a few feet from a massive
ravine.
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Even if you try to help, almost none will believe your little light works better than
the larger lightshow of the collectively credulous circus.
Let me ask you a question…
Is it possible – even remotely possible– that perhaps our perception and digestion of, and
action upon much of the information we have been taught to believe as accurate and
reliable…may have been flawed from the start?
Let me tell you about a guy I know; he's perhaps not the brightest of the bunch…
He is a trader though, and he has never done anything else his entire career. When I
asked him why he trades for a living, his reply was:
"To make $40 billion dollars beating markets."
In reality, 'not so bright guy' is me.
I'm still a long, long, way from my goal of $40 billion, but with the information in
this book (and years of experience and disciplined money management) I believe I will
someday make my $40 billion goal real. Why do I yearn for $40 billion dollars?
Because I've always had another dream:
Buy a black jet; paint a 'skull and crossbones' on the tailfin and fly around the world
giving $39 billion away to help people...all people.
Perhaps I'm crazy...
Regardless of sanity, in pursuit of turning the previously mentioned dreams into
reality, I have chosen trading as my genie of action.
Over the years, one major heartache I've found (actually trading for a living) is
when one rubs markets three times, the only thing that comes out of the 'wishful
thinking market lamp' is a margin call… Not a dude in tights joyfully granting three
wishes. In my time, I've seen more grown men cry on trading floors than I care to
remember. I've also seen one make hundreds of millions of dollars. I am not the 'one'
yet, but I intend to be.
With all of this in mind, the information you are about to read in the following
pages was derived from countless hours grinding it out with the market, in an effort to
create my own magic lamp. What I'm talking about is the culling of thousands of hours
of research, real-time trading (I do not back test, or trade demo to prove a strategy),
breakouts, blowouts, headaches, elation and in the end, insights that I would have
never found without having taken the rocky, unstable, non-traditional route that I
have.
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After just short of 4,500 days of eating, sleeping and breathing markets; after endless
research, writing, analysis and of course trading – at the ripe old age of 35 – I possess
something more than a head full of gray hair…
I have a hidden treasure.
– A very special light, really.
As hidden treasure goes, often very few know it exists, when it does exist, which is
why it was so hard to find...
Because I had to find it myself...
If there were others I crossed along the way who already knew, they didn't let on.
And I understand why one would want to protect knowledge of the treasure's
existence, and location.
Not many people seek to give their money away, just to give it away.
For those who do know of the treasure's existence though, sometimes they even
intentionally burn their maps to keep others from coming into possession of
information containing the whereabouts.
Without a map, the chances of finding the treasure are virtually zero, especially
when one doesn't know to even look for it in the first place. What's more, for those
who are seeking the treasure, sometimes even when they're standing directly over it,
they still won't be able to see it.
That's how it was when I began looking…
Every once in a while over the years though, I would unexpectedly catch glimpse of
an amazing shimmer within markets; something so bold, luminescent and brilliant, I
would stop everything to investigate it.
But it was always gone in a brief second.
By the time I located what I thought was the source, no evidence of the glow
remained.
The light was so brilliantly overwhelming though, I simply couldn't get it out of my
mind's eye. I began looking for the magnificent illumination each day...and
night...sometimes not sleeping for two, and even three days at a time.
Many of those around me wondered if I might be going slightly nuts...
A few times, I think I might have wondered too.
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I even spent the entire month of November in 2008 at the World Trade Center in
Guangzhou, China working with several programmers and traders on the trading floor
of ECTrader to develop and code the information I'd uncovered to that point...
This fall, I'll travel half way around the world to work the Chinese traders and
programmers again... Not only are they some of the nicest guys in the entire world, but
I've never met better programmers...ever.
Even after China, I was still missing few critical pieces though... But over this past
winter and spring...
I finally compiled enough information to clearly see Volatility Illuminated in a way
the masses have yet to.
I can tell you this... Towards the end, it was almost as if daylight were growing
from the horizon, after a long dark night... Before I completely realized it, there was
light everywhere.
In my arduous search over the years, there were moments so difficult; I almost gave
up many, many times. Honestly, the search to see Volatility Illuminated was so
grueling; I sometimes wonder how I made it through, without quitting.
You don't have to go through what I did though... And I hope you don't. And
won't.
It is my hope that with the information in this book, you will be able to clearly see
Volatility Illuminated, without having to endure all that I did.
While compiling this book, I've asked myself at least a dozen times, why I'm giving
up any of the information I've found? My search was arduous and at times – literally –
painful...
Strangely, every moment along the way, both good and bad, was the precise event
required to dislodge (sometimes in the most unexpected of places too!) a little piece of
information that I desperately needed to take another step forward with Volatility
Illuminated...
Even an understanding of why Superman wears his underpants on the outside...
Again though, I have asked myself repeatedly why I'm giving up what I worked so
hard to find?
1. I am presenting the information here because I believe I can say with a confident
voice, most have never seen Volatility Illuminated before, at least, as I will present
here. In addition, I believe retail traders sorely need the information right now.
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2. I'm a trader. I trade for a living. Writing this book is a trade too. You get
information, I get money. If I blow up doing something stupid five years from
now, thankfully I will have hedged my position with a few bucks from these
words.
I think it's a good trade... And by laying size out at the offer, obviously, with all of
my years of sacrifice, research, and hard work, I'm long Volatility Illuminated. Now,
I'm offering out of some of my position into strength, precisely into the upper 3.2
standard deviation of the long-term distribution. If the demand the tape has shown in
the last few days of May is real, I may later regret not lifting my offer higher - now - but
for the time being, I think it's fair.
Yup, everything is a trade.
I can't say I'm putting absolutely everything I've discovered in these pages…but it is
definitely enough…
Likely, more than enough to finally give the little guy...
The retail trader...
– Something of value to help level the playing field in today's media-mania, monster
truck institutional orderflow markets.
On another note, I am almost certain those in the financial media do not know about
the treasure you're to going learn here… Otherwise, they would have already brought
it to the market's attention. I've heard a few pundits lightly brush on one aspect of the
treasure or another – almost as if they'd sensed it was there, but I do not believe any
have ever found it (or even heard of it) completely.
Moreover, I believe there are a few great investors and market minds 'in the know'
about the concepts to follow…though likely keeping quiet.
What's more, in my research, I've come across various pieces of the treasure here
and there, but I have never found much compiled all in one place…in an easily
understandable format. What little of the treasure I have heard mentioned in
conversations and radio, caught glimpse of on television, spied in magazines or
newspapers, or found on the Internet – was not (I do not believe) geared for, or meant
to grab the attention of retail traders.
Before we go too far, I need to give you a few warnings about the treasure in this
book…
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 It won't make you instantly rich this hour, but it could over time.
 You can't sell it on eBay today, but you can try.
 You cannot take the treasure all for yourself, though many people would.
 You cannot horde it in your upstairs closet at home; it won't fit in a shoebox.
 The treasure (by itself) likely won't even buy you a hotdog on the corner, but
someone might offer to give you all the hotdogs in the world just to know what it is.
I would like to mention something else… You will not be able to see the treasure at
all, if you only want a 'gimmick' to make money quickly. The treasure is not a
'gimmick'...it is real...but to see it, you must have the desire to truly understand
markets and trading.
While writing this book, I often handed the manuscript to a small handful of 'test
readers' for feedback. One of the test readers made a comment similar to:
"You may want to remove, or change the bullets about it won't make you rich and
you can't sell it on eBay, because some people might think 'well what good is it then?' or
'I don't want to waste my time then' and then you might lose some readers."
I really appreciated the comment, because my friend was truly attempting to step
into the shoes of the masses… I thought about removing the seemingly self-defeating
bullets, but then concluded I would not.
Why?
Because my friend's perception of many potential reader's likely fickleness was spot
on. However, the reason the treasure remains buried day-after-day, month-aftermonth and year-after-year to media, retail traders, analysts, and the public is precisely
in the comment itself.
The treasure has remained hidden because one will not be able see it if they are only
seeking an easy, automated, 'no effort', instant gratification solution to markets.
The treasure is mostly invisible to the retail eye because upon first glance, it appears
worthless, though really, it holds immense potential riches and value.
The treasure is not simple; yet it's also not so complicated that almost anyone can't
understand, or use it.
The only people who will not be able to see or use the treasure are those who never
wanted to see it in the first place. The desire to see Volatility Illuminated, means you
must have already...somehow...wanted to know (and see) markets better. Those who
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have never truly desired to understand markets and trading (and were not willing to
put in some good old-fashioned hard work) just wouldn't know to even look for
Volatility Illuminated in the first place.
 Media only cares about being in the middle of a 'hot story' and most pundits and
analysts never really trade their own money…
 The bulk of retail traders hardly ever really 'think' about information they receive
and act upon, and rarely truly attempt to learn fundamentals of markets...
 Many investors seek something, or someone to do the work for them…
 Often, if retail traders, professionals, and/or media can't see value in something
instantly, they throw it away…
Thus, the treasure is most often invisible to the common eye.
I bet many readers have personally walked by it a dozen times and never even
sensed something amazing might be nearby.
I know I did. On a rare occasion, I still do.
The treasure is so obvious though, once you see it, you might ask how you missed it
all this time?
It is possible; however, that even after reading this book, some still will not be able
to see it, even if I directly point it out, as best I possibly can.
How could it even be feasible for an 'obvious' trading treasure to exist, as I am
mentioning here (something of great potential value), right infront of all of our eyes,
and yet invisible to the masses?
My conclusion is the treasure remains invisible to the masses, because to see it (and
to use it) means one must first not only have the desire to see it, but also acknowledge
that the common perception of the information we receive (as even 'mostly valid')
could be flawed...
 Wrong about the information we accept daily.
 Wrong believing what we've been taught is accurate.
 Possibly wrong about some of the things we think and feel at this exact moment.
 Maybe even wrong about our own memories right now.
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How many are now thinking, "…that sounds fascinating, please show me"?
And how many are really thinking, "Are you crazy? Whatever, this is hocus-pocus. My
memories have nothing to do with markets."
Like the masses were historically wrong about the world being flat, the sun
revolving around the earth and wrong about slavery, as being even remotely
acceptable or moral, before the final Emancipation Proclamation and 13th Amendment
came to life in 1865.1
(By the way, the 1860 United States consensus showed 393,975 individuals owned
3,950,528 slaves. The 1860 document also shows that there were just over 31 million
people in the population. Only 8% of the population owned slaves.2 What the
aforesaid means is (as always) a small percentage of wealthy corrupt, sway the
opinions of the masses and hold the majority of power in society, economics and
politics.)
Much like the masses thought the world economy was absolutely doomed after the
crash in October 1973, especially as major indices skidded south into the end of 1974.
But in January of 1975, markets rocketed higher.3
Probably why Warren Buffet, the brilliant and amazing investor often says, "Buy
when others are fearful and sell when others are greedy."4
Much why many will happily repeat Buffet's words, but then never act on the
advice personally.
To step apart from the masses, one needs to take action.
Almost everyone tells children to follow their dreams, but so few truly do as adults.
Even after I show you the treasure, it will take time and effort to unlock the power
within. Volatility Illuminated will not work instantly for those who want nothing more
than a lotto-ticket, or 'plug-and-play indicator' -so they can mindlessly know when to
buy and sell, without really adding any effort.
However, if you truly desire to see Volatility Illuminated and you're willing to put
considerable effort into understanding the 'philosophy' behind such, the greater your
chances of using the treasure to pull millions out of markets.
To see Volatility Illuminated though (and then utilize the information effectively) a
paradigm shift will likely be required in your mind. No matter how hard I try, I can't
help you see it if you totally believe what you've been taught about markets and
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trading (in terms of fundamentals, technical analysis and information), is absolutely
right and proper.
Just know this, if you're willing to open you mind, please don't fear Volatility
Illuminated may be too complicated to comprehend. I am proof of the pudding that
you don't have to be a rocket scientist to get it. I am also virtually certain you don't
need to be a seasoned Wall Street pro, or even college educated, for that matter…
All you need is the ability and willingness to challenge the traditional paradigms of
what you have been taught about investing, markets and trading in today's high-tech,
'light-speed information' world.
Again, in Volatility Illuminated, I hope to completely change the way you look at
trading and markets and I seek to give you the tools you need to trade perceptively and
profitably.
I have put hundreds of hours into the theories, concepts and strategies you are
about to read. Moreover, I've spent nearly as much time tactically planning and
organizing how to convey the information to you in this book. I did not write this book
just to write a book. This book was written to deliver concepts to the masses that have
been missed, overlooked, held back, or simply not discovered to date.
With this in mind, every word, every sentence, paragraph and chapter has a specific
reason for its placement within the larger work.
In Part One, we will cover some basic groundwork behind Volatility Illuminated,
flushing out why some of what we accept as truth is not, while also seeing how
instances of fundamental and technical analysis can be helpful to our trading, but really
require more.
In Chapter Two, we will discuss why technical indicators are built for failure, are
indeed currently failing, and how you can overcome the destructive reality at hand by
taking time to step back from markets with clear eyes. We will also touch on why and
how technology is really creating a larger 'blind mass', rather than helping.
Next, in Chapter Three we will cover why the much of what we think we know
could be an illusion. I'm talking about our own memories even. I hope to challenge our
unquestioning acceptance of our understanding and perceptions, not only of our own
minds, but the reasoning and sensibility behind much of the information we take in
daily.
In the remainder of Part One, we will walk through two technical strategies
(Fibonacci Pitchforks and Quad-CCI Momentum) that I've found work reasonably well.
However, I won't just present the positive aspects of Fibonacci Pitchforks and Quad
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CCI, but also seek to show how at times, almost all pure technical analysis breaks
down. It is here that we will open the door to volatility, probability and the movement
of distributions (statistics).
By the end of Part One, you should have moments of excitement, coupled with
questions about whether anything 'really works' in this book, markets and/or in
attempting to see and predict volatility.
Then, in Part Two, we will dive into descriptive statistics (in terms of distributions),
while tackling volatility and probability right away.
In Part Two, I seek to not only present Volatility Illuminated in an easy-tounderstand format (for those who do not have hordes of experience), but I also hope to
show why tenured traders may want to rethink some of what they've been taught to
believe as truths of information, markets, trading and volatility, as well.
I will also present some theoretical ideas combining physics and markets...
Don't worry though, no calculus or math will be required.
As you will see though, through Einstein's Theory of Special Relativity, I will prove
that the entire paradigm of information colliding with markets has changed, partially
through the acceleration of information over the past 100 years.
As we move through the first chapters of Part Two, you will also begin to learn why
and how mass, acceleration, force and energy all 'critically' apply to today's markets
and trading.
Again, you won't need to understand the math, but readers absolutely must take the
time to understand the philosophy and theoretical modeling behind the concepts
within Volatility Illuminated. I have done my best to explain the entire paradigm in
plain, everyday language.
In addition, we will also combine physics (specifically mass, acceleration, force, and
energy) with volatility, probability, subset distributions, and institutional
benchmarking to form Whistler Volume Adjusted Volatility (WVAV) and Whistler
Active Volatility Energy • Price Mass (WAVE • PM.)
The information you are about to read is not a regurgitation of old ideas, like most
books on trading.
The ideas presented in Volatility Illuminated are fresh, groundbreaking, innovative,
and are really my life's work.
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Moving on, in Part Two, our discussions will move from physics to
volatility/probability and distributions...opening the door to institutional
benchmarking and VWAP.
The information on VWAP is intended to be delivered in a humorous format,
though really, could be game changing for most readers.
After many, many hours thinking how to present the information to you, I finally
came up with the story of Captain BIOVAP and Doctor Watermelon Stuffer, as the
relay. (Trust me, if I explained it from a professional technical market perspective, not
only would 70% of readers not get it, but the other 30% would be asleep by the time I
was finished...)
However, do not take the information lightly.
Really, 'the theory of stuffing watermelons into mufflers' is why most retail traders
lose.
Fact is, they never understood the game from the start. When you understand
Doctor Watermelon Stuffer, you understand institutional trading.
With the aforementioned in mind, we will then break into WVAV and WAVE • PM.
My intent with WVAV is to show how and why we can integrate mass/energy
concepts into VWAP, thus locating levels of volatility and probability, possibly
providing insights many institutional traders have even missed.
The concepts you are about to read about are designed to help all traders; meaning
both institutional and retail.
I will also show how and why WVAV and WAVE • PM allows one to see when
markets are about to trend, when trending has ended, and even when to expect
consolidation.
Through WVAV and WAVE • PM, readers will learn probability trading,
perceiving volatility and orderflow (ahead of the game) and perhaps most important:
how to use the information within real day-to-day trading.
By the end of Volatility Illuminated, you will posses information about indicator
and information failure, volatility and probability, institutional orderflow, mass,
energy and force in markets and distributions – all pulled together in a simple,
understandable format and methodology...
You will understand what Whistler Volume Adjusted Volatility (WVAV) and
Whistler Active Volatility Energy • Price Mass (WAVE • PM) are, while also seeing
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why the totality of the entire paradigm; the strategy, methodology, theory, philosophy,
and signals are like nothing else markets have ever encountered...
You are about to set eyes on the critical underpinnings of market movements and
trading – which virtually all media, retail investors and professionals never, ever see.
What you are about to read is powerful, useful, actually works in real time and can
help you succeed in trading once and for all.
But you MUST be willing to consider that everything you've been taught to date…is
skewed.
Now that you know what to expect in the pages to come, I'm very excited to explain:
...why Superman wears his underpants on the outside...
...and also, why it matters so much to you...right now...
...as you're about to discover...
You may want to consider wearing your underpants on the outside as well…
The majority is always wrong –
Especially retail traders
The 19th Century playwright Henrik Ibsen penned:
"The majority is always wrong."
Again, the 'majority' thought the sun circled the earth before Galileo.
The 'majority' thought the world was flat before the days of Columbus, even though
other great thinkers had shown evidence of a sphere planet long before.
Around 330 BCE Aristotle surmised the earth was round and in 240 BCE,
Eratosthenes created a reasonable estimate of the earth's circumference…
And yet, the masses still believed the earth was flat for almost 2,000 years more.
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It would be rude to say something like, 'people are cattle', which would never surface
in the pages of Volatility Illuminated. After all, a statement like 'people are cattle' would
infer the masses simply move when prompted to do so, by almost nothing more than
the directional stampeding of the larger group.
Actual people couldn't possibly be that mindless could they?
Would you ever mindlessly accept news or even [gasp!] believe in a mainstream
media opinion, simply because the bulk of society had accepted the information as
valid?
It's hard to believe for one moment, human beings might be that silly. People
would never credulously accept inaccurate social, political, or economic trends,
merely because such had become 'progressive', or the 'accepted standard', would
they?
However, with each passing day and every laborious hour of research, I begin to
believe they would. At the end of the day, the majority is almost always…wrong.
Perhaps, it's not completely the larger group's fault though. The more I look at the
totality of information delivered to investors and traders; I see where and how they
have been set up for failure (within trading and markets, economics and politics) from
the start.
I'm not just talking about Forex either; I'm talking about all markets.
Some people refer to the phenomenon of the general investing public seemingly
always on the losing end of the stick, as proof trading is nothing more than a 'zero sum
game'.
Perhaps the common perception that markets truly are a 'zero sum game' is
precisely correct, for those who've never been exposed to any information, other than
the noxious rattling of media and so called 'professionals' who have an agenda.
Consider this for a moment:
If one eats apples from a tree with poisonous roots, chances are the apple is
poisonous too, right?
After all, a poison tree probably only produces poison apples…
For the average investor (in the short run) the apples sure look pretty though and
they're just so tasty, investors keep going back for more – even if they'd fallen sick from
eating the apples once before.
The tree, like all trees, follows the seasons though. The tree blooms in spring, grows
luscious apples during the summer, sheds its fruit in fall, and then grows dormant
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when the coldness of winter arrives. Spring always comes back though, even if the
winter was longer than most on record.
When spring does finally arrive, media is always there to tell the world about the
new fruit budding.
Investors are reluctant at first, remembering the sour fruit that had made them so
sick the previous season…
Many are even still recovering from the poison they couldn't digest, or barf out…
But the media is there – touting the trees and the season, often reporting this season
could be the best and longest and safest yet.
However, smart money already staked claims on many trees and their potential
production in late winter, or early spring, often before the 'season' of today was even in
the minds of most.
As summer unfolds and the apples begin to take form, media comments on how
they look tastier than ever. While the apples are developing, they're not poisonous
though, as shown by media gorging on the fruit as quickly as it can, while touting to
the world how delicious and safe they are this time around.
At this point, the lure of the flavorsome fruit is becoming irresistible for most…
Towards the end of the summer, media is at the harvest in full force touting 'the
grandest bloom yet', while also mentioning that this season's apples are not only the
safest ever, but could still grow even larger.
Media even starts to present the possibility winter may never come again. Finally,
giving into the media bolstered temptation – investors can't resist any longer. They
buy apples...hordes of apples.
But the apples have a secret…
The apples from the poisoned trees are safe to eat only so long as the temperature
remains warm…
But when the first cold sets in, the cores release a deadly toxin into the meat of the
fruit.
Those who were the last to buy don't have a clue what just happened under the
surface of their purchase, as they bite in…
Sometimes, even institutions buy tainted fruit too, thinking they know better than
the public where the poisoned fruit is, and is not. But they're wrong too.
So I ask, why do the people keep buying apples from the exact same tree that
produced poisonous fruit the previous season?
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And then, I have to ask an even more important question…
In the paragraphs you have just read, did you… even for a moment…consider that
perhaps it was not the tree, or the apples, or even the roots, which were truly
poisonous…
Perhaps the tree wasn't really poisonous at all…
But the soil the tree is growing from…is.
The Principle of Buoyancy IN
MARKETS
I believe that back testing is a joke. Everyone has perfect 20/20 hindsight. Thus, in
developing the trading strategies here (from a retail perspective); I made sure to test
each and every one with real money. I'm not going to barf out a win/loss percentage,
Sharpe Ratio, or any of the other canned junk people use to bolster whatever it is they
are selling…
Because all that matters is today. Right here...right now. Past results are no
indication, or guarantee, of future performance.
This book is not about a 'system', this book is about truly learning markets and
becoming skilled at seeing Volatility Illuminated, once and for all. Moreover, in my
humble opinion, learning to trade comes down to the quote:
The law of flotation was not discovered by contemplating the
sinking of things, but by contemplating the floating of things
which floated naturally, and then intelligently asking why they
did so."
- Thomas Troward
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Interesting quote right? Right. Except that at times, it's the opposite of trading. I
hate to say it, but without a clear understanding of why what's happening is
happening, trading is the opposite of buoyancy.
The reality of the situation is:
Traders and investors have a limited amount of time and money; however, markets
have an unlimited amount of time and volatility.
If you simply toss your money into markets, thinking you've picked a safe entry and
given your position a liberal stop, just so you won't be unnecessarily taken out and
then step away… Chances are, markets will...eventually...hit your stop, or produce a
margin call, much sooner than your sanity and/or wealth can 'wait out' the pain of a
massive pullback.
I remember a long time ago, just after I started trading; I hit a three-month rough
patch where I couldn't seem to make a decent trade to save my life. One day, angry,
upset and whinny, I decided to just flip a coin during the entire US session and take my
trades in whatever direction the coin prompted.
My theory was this: I should have a 50/50 shot, up or down, in picking the
direction of my trades. However, I also figured my odds would be even better because
I have something 50/50 probability does not account for: money management skills.
I figured even if I didn't like the trade, I could just place a strategic stop (cutting
losses quick and letting winners run) and I'd surely come out ahead in the end.
Nope. I was just about even on the day…but it was a painful even.
See, if you don't have a real reason to be in the trade from the start, you won't have a
solid reason to know when to get out. (And vice versa really.)
Anyway, randomly tossing cash into markets is more like 'the theory of sinking
things', over that of buoyancy.
Here's what I want to tell you about the concepts coming in Volatility Illuminated…
Over the years, I have taken some big losses to uncover the information you are
reading… I'm not even going to talk about the wins, because in the latter half of the
book, you will see where, how and why the principles work. I don't need to tout what
most people only do – past wins.
But I will touch on the losses – because they are what matters most to see Volatility
Illuminated…
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I've already 'contemplated the theory of floatation' for you…and as we roll out the
principles of Volatility Illuminated over the following pages, you will see likely what
works, without me having to run my mouth about my winners. If I were to only
discuss my wins, the occurrence would be like giving you a set of keys to a
supercharged 357 Mustang and an open highway, but then forgetting to mention the car
has no brakes.
Throughout the years, as I was developing all that you're reading, every single time
I lost, I would ask myself a massive pile of questions, in an attempt to uncover why the
trade did not work.
Every single time I went through my little self-interrogation (with honesty) I
constantly found one question as the main culprit behind almost all losses:
Was my information wrong?
There's really only two answers to the above:
1. Yes, my information was faulted, and/or…
2. My information was correct, but my understanding and application of the
information was not.
Amazingly, it was the question, "Was my information wrong?" that not only caused
many headaches, but was the catalyst for success.
It was the sinking of things that brought the volatility theories of flotation (which
you're reading right now!) to light.
Again, it was in constantly asking the one question (that produced two more
questions ) that unearthed the hidden and mysterious volatility within markets that
often plagues most traders for all of their days.
Funny thing those old self-introspection and honesty questions; here's what they
produce:
Growth.
In the end, I not only found answers to why and how retail traders lose, but I also
discovered the answer to, why Superman wears his underpants on the outside too.
The answer is this:
Superman wears his underpants on the outside because really, he knows he can beat
up anyone who makes fun of him for wearing Underoos™ on the outside of his pants.
Just kidding…
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Really, Superman wears his underpants on the outside because he is the inverse of
mass humanity. Superman is everything we are not. Superman is the inverse of greed,
ego, fear, dishonesty... All the things that keep retail traders from winning big.
Unfortunately, as regular people we are not, "Faster than a speeding bullet, more
powerful than a locomotive, or able to leap tall buildings in a single bound."
But Superman is…
Hold on a second though… We might actually be able to do the marvelous things
Superman does… What I mean is…how do you know for sure you can't? Have you
ever tried?
With your underpants on the outside of your slacks?
Regardless if you've ever run down the street next to a passing locomotive –with your
underwear atop your jeans, please know this…
In essence, we are penetrable organs and bones on the inside, while the world is
seemingly impenetrable (to us) on the outside.
Superman is the opposite, impenetrable on the inside, and penetrable to the world
from the outside.
Superman, as a walking bag of biology, is stronger than the world surrounding his
physical form.
Logically, we can diagram Superman in relation to the outside world as:
Body → Pants → Underpants → World
On the other hand, we can diagram regular people (non-superheroes) in relation to
the exterior world as:
Body → Underpants → Pants → World
or
World → Pants → Underpants → Body
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Do you see what I'm saying?
Let me break it down, just in case…
What we are: Breakable.
What Superman is not: Breakable.
What we are: Slow, brash, opinionated, and mortal.
What Superman is not: Slow, brash, opinionated, and mortal.
What we are: Stuck on the belief our underpants should go on the inside of our jeans.
What Superman is not: Stuck on the belief his underpants should go on the inside
of his trousers.
It makes sense that as metaphor of Superman's extreme difference to regular
humanity is his preferred order of underpants, relative to what most people would
ever consider in their own lives. Precisely what most would scoff at others for
considering, or doing…
Here's where I'm going with all this underpants business…
To truly understand why much of the information we believe to be valid within
trading and markets is flawed, we have to be willing to invert what we have
previously accepted as valid.
What I'm saying is that metaphorically, if we want to understand volatility and
markets, we must be willing to consider the possibility that what we have learned and
believe as 'truth' and/or 'the right way', may not be so correct after all.
Again, let me clarify. . .
I'm not saying the information you have received is just plain wrong…
What I am proposing is perhaps a different paradigm exists within trading, markets,
and the validity of information we accept from mainstream media, and to transcend
and evolve in our ability to comprehend, predict, and profit within Forex, equities,
options, futures, whatever…we must be willing to accept an inversion of what we have
come to know as truth.
Perhaps, what we believe to be true right now, may not be.
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To see where and how some of the information we receive and accept within
markets may be faulted, we must be open minded enough to accept new paradigms.
If we can remain open to new ideas, we might be amazed at what we are about to
find in the following pages.
Bottom Line: If you want to be a superhero, you're going to have to be willing to
wear your underpants on the outside, knowing you are doing precisely the opposite of
what the masses believe is valid and/or acceptable. Again, 'the majority is always
wrong', which is why they wear their underpants on the inside.
The masses believe that 'underpants on the inside' is the only way to go about day-today business. The 'underpants on the inside' crowd even laughs at anyone who wears
their drawers on the outside.
Those who wear their underpants on the outside...have superpowers. Mr. BVD's
atop khakis and Ms. Brassiere over blouse can fly.
The undergarment-rerouted-to-the-exterior minority, are really the inversion of
credulous, blind and herd-following masses, who simply accept common dogma as
truth because it is the accepted standard, even though it's wrong.
Super-traders know much of the information presented to the masses…is
flawed…especially when it comes to markets. Most retail traders and investors are the
inverse of super, which is why so many lose in markets…and then even keep coming
back for more, again and again, without ever questioning what's really happening
under the surface.
With the aforementioned in mind, we will now move into Chapter Two, where we
will discuss how many technical indicators are failing in the current market, while
uncovering why so many traders are likely suffering, when attempting to trade simply
from common technicals.
Chapter Two will open our initial discussion on volatility, though we will only
scratch the surface for the time being. Then, in Chapters Three and Four, we will cover
two technical combinations (Fibonacci Pitchforks and Quad CCI), discussing how the
indicators help traders, while also touching on why current market volatility could be
causing false signals as well. Over the following pages, I ask you to break from what
you currently believe as valid and true, concerning information, indicators, and
markets…
I'm pleading…
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If even for a moment, while reading this book, please wear your
underpants on the outside, like Superman.
At least, metaphorically, anyway…
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CHAPTER TWO
WHY INDICATORS ARE FAILING IN THE
CURRENT MARKET
The initial version of this chapter was printed in Forex Journal in the spring of 2009, but has
been revised significantly since.
When it comes to trading Forex, it's no secret retail traders struggle desperately and
most often, lose. The aforementioned statement is dismal, I know.
However, it doesn't have to be that way…
With a little understanding of "why" retail traders seemingly (endlessly) toil, shifting
the paradigm may actually be easier than many think. In short, when we truly take a
moment to step back from technical trading and examine how information and
indicators impact the decisions of the masses, a clear picture of why traditional chartbased signals are 'built for failure' from the start, should arise.
By understanding the true paradigm of technicals, and then making a few slight
adjustments, traders could potentially find themselves suddenly empowered to
navigate markets with confidence and clarity.
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Retail versus Institution
Separate Takes - Same Information
Foremost, it is important to note that institutions move markets, not retail traders.
However, with many institutional and retail traders acting at similar time, it would
almost seem as if they were trading from the same signals. Upon first glance, it would
appear as if traditional indicators do indeed provide reliable signals for market
movements.
In reality though, traditional indicators (like MACD, Stochastics and CCI) are
providing "false signals", especially on shorter-term time frames. Institutional order
flow has nothing to do with 'technical signals' and is truly derived from perceived risk
aversion and future fundamentals.
Despite the reality at hand, some retail traders continue to believe traditional
technical analysis accurately looks into the fundamental mindset. What you MUST
understand though, is common retail technicals have nothing (at all!) to do with
institutional trading and do not accurately look into the minds of institutional traders.
At the core of the issue, common technicals never accurately see into the minds of
institutions, simply because the technicals are derived from an empirical event that has
already occurred (lagging indicator) within price action, while fundamentals attempt to
mitigate fundamental risk of today, while attempting to step in ahead of possible
fundamental events of tomorrow.
Retail traders often lose, because even if they are able to perceptively step into the
minds of institutions, trading successfully commands the trader is not only able to see
the true fundamental paradigm, but also know when and where to implement a
position to capitalize on such. In non-technical language, one may be able to accurately
distinguish that a particular currency will lose value over the next year because of
deterioration in fundamentals; however, successfully acting on the information is
much, much more difficult, when considering the inherent volatility within Forex
markets today. Looking at our first image, readers will note the significant rally in the
EUR/USD into December 2008. The euro's momentary recovery can be attributed to a
dead cat bounce from torrid selling in the previous months, coupled with the
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momentary loss of belief the US Dollar would continue to avert risk throughout the
global economic crisis.
Conspicuously, even if traders were able to accurately predict the U.S. Dollar was
about to boldly recover from late fall rally in the euro, blindly taking a position could
have been devastating, if implemented based on fundamental outlook alone. The
single daily candle highlighted in late December shows almost 400 PIPs of volatility,
which should serve as empirical evidence of the excessive volatility at hand within
Forex markets.
The larger issue is simply while institutions and retail traders may have unearthed
similar fundamental information (though often institutions have greater clarity) retail
traders who act on technicals or fundamentals alone, will constantly fall victim to the
inherent volatility within Forex today.
What's more, the indicators retail traders act upon
are often significantly different than that of
institutional traders, something many are not even
aware of.
For example, when looking at descriptions of
services banks and institutional companies provide
for larger FX participants, one will note the first two
technical strategies/indicators are almost always
Volume Weighted Average Price (VWAP) and Time
Weighted Average Price (TWAP).
However, the charting packages most retail traders
use almost never contain VWAP and TWAP, as
indicators. In fact, even MetaTrader (arguably the
retail standard), does not contain VWAP and TWAP
preloaded.
Traders can find the code in the back of this book, on the Internet, and on my
Websites fxVolatility.com and WallStreetRockStar.com; however, the aforementioned
are not delivered already installed within the software's various custom and traditional
indicators.
The point here is the main indicators institutional traders are not only looking at, but
also acting upon, are rarely visible within the retail trader's world. Most often the retail
trader must actually intentionally seek out the indicators; but how can one find what
one does not even know exists?
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There's even more to the story, and as readers are about to witness, the paradigm
behind retail technical analysis may have been flawed from the start. Even worse, the
common technical indicators most retail traders covet could even show greater
amounts of false signals in the future.
Lock, Stock and Dogma
To understand why technical indicators are becoming more and more troublesome
in volatile markets, one must take a step back from the entire situation and examine the
"nuts and bolts" of the larger situation at hand.
Constance Brown just about says it all in her book titled Technical Analysis for the
Trading Professional (McGraw Hill, 1999), where she asks:
"Why does it appear to us that conventional technical indicators
are failing us as we approach the 21st Century? What has
changed?"
- Constance Brown
Technical Analysis for the Trading Professional
As a brief side note, while Brown's book is almost a decade old, the information is
still extremely innovative, as she often examines the "truth" behind how and why
indicators produce signals. Even more important, Brown also attempts to uncover how
and why traders act on the information received.
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In the case of failing technical indicators, Brown hypothesizes technical indicators
are failing because too many people are acting on the same information, at the same
time. She points out virtually every charting program comes with the same pre-loaded
indicators, with the same pre-set variables. What's more, she also unmasks the
unfortunate reality that many traders never even bother to question, or change the
preset variables within the pre-loaded indicators. In essence, traders simply accept
the "factory settings" within their indicators as dogma.
At first glance, it would seem common sense that many people acting on the same
information, at the same time, would create a sort of 'self-fulfilling prophecy' within
technical signals. However, the reality of the situation proves differently. Really, some
people acting on the same information at the same time may create a slight amount of
'self fulfilling prophecy'; however, when too many people move in the same direction,
at the same time, the real outcome is volatility. Think of it like this: If a troop of ten
men run are running on the street together and suddenly need to stop before a busy
street, all ten will likely be able to do so. However, if 1,000 men are running on a street
and a few in front attempt to stop before a busy street, the mass of bodies in motion
behind the will likely bump into one another, with the greater whole pushing the few
in the front into the intersection. Someone call a paramedic.
Why would trading be any different? When a hundred thousand traders take the
same position, at the same time, based on the same information, and suddenly the
market moves just slightly opposite the herd's expectation, what will the obvious
outcome be?
You probably guessed it; the large mass-herd of traders moving in unison creates a
pop of volatility as the collective whole attempts to switch directions.
Making matters worse, once the herd is pushed slightly into the intersection;
electronic stop orders begin tripping across the world, like grids of lights rolling into
darkness, as a mass blackout ensues. The "mass effect" of too many people acting on
the same information, coupled with the domino effect of electronic stop orders being
tripped globally, creates excessive volatility within intraday trading.
While retail traders do not carry enough weight to propagate an all out "trend" in
the world of Forex, they do create short-term volatility. I like to call it Herd Induced
Intraday Volatility, or the "HIIV Effect."
Retail traders move like a swarm of bees and so when I see a clear signal from a
common technical indicator on a 5, 15, or 30-minute chart, I look for the HIIV effect of
volatility to begin stinging.
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By the way, with stop order rule changes coming (for U.S. retail Forex platforms) in
July of 2009, the 'rolling blackout volatility' effect could wane, while overall reversal
volatility could increase as traders hold losing positions as long as possible (it's just
human psychology) until major critical technical points are hit.
While the removal of stop orders in U.S. trading platforms may help bolster longer
periods of trending, major points reversal points could surface with fierce volatility…
HIIV Effect in Action
For traders having trouble believing the
technical 'herd effect' I previously described
actually exists, please take note of the
following example.
(By the way, one needs to do nothing more
than scan 5, 15 and 30-minute charts to
discover plenty of examples of the HIIV
effect.)
Looking at Figure 2.2, traders will notice
the 30-minute chart is clearly showing signs
of a potential reversal pending, at least in
terms of traditional technical indicators, like
candlesticks and stochastics.
One cannot miss (even for a second) the
fact that the 30-minute chart is displaying
three bearish candles (two red hangmen
and one evening star).
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In addition, using the pre-loaded stochastic indicator (5, 3, 3) traders see a clear
cross of the K-period (blue) under the D-period (red).
The aforementioned stochastics cross-under is occurring at the 80-line, the exact
point many technicians believe produces a reversal.
Seems like a clear short-entry point right?
Hmm…
Look at Figure 2.3, which shows the EUR/USD rallied significantly after the
appearance of the two hangmen, one evening star and a stochastics +80 cross-under.
There are two events occurring in this scenario:
First, institutional order-flow (read: fundamental mindset) likely believed the carry
trade differential and risk facing oversold levels of the EUR/USD were prompting
short covering and short-term relative range trend continuation, if even only for a
moment.
Second, when the false
signals appeared, many retail
traders likely took short
positions, expecting a larger
reversal to ensue.
However, when the reversal
did not show, those same
traders were forced to cover
positions…en masse, thus
helping fuel the torrid bull
candle eight bars after our short
signals (Figure 2.3). Often,
when false signals surface, we
see a slight amount of "wiggle"
shortly after, while traders and
institutions attempt to decipher
the reality of the situation. As
the dust begins to settle though
and traders realize the technical
indicator was false, a sharp
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move occurs as panic sets in.
Again, the panic HIIV effect can be seen in Figure 2.3, eight bars after the final false
hangman short signal.
The EUR/USD quickly (and sharply) rallied from the 1.3580 (roughly) area to the
1.3680 region in one 30-minute bar.
For the EUR/USD the aforementioned pop is 'faster than usual', thus we can infer
many traders were caught going the wrong way.
What's more, Figure 2.3 also shows stochastics trending downward during the bulk
of the ensuing upward momentum, even after the false signals appeared.
Does all of this mean technical indicators can no longer be trusted whatsoever?
Not necessarily; however, there are a few critical points to consider. Foremost,
common sense tells us that most retail traders attempt to take intraday positions,
without taking much notice of long-term fundamentals. What this means is many
traders likely take positions against the larger-trend, simply because their
misunderstanding (or lack of will to do the proper research) hinders the mass
contingency of "at home traders" from seeing the situation clearly. Moreover, retail
traders often watch shorter-term timeframes, more often than they take note of the 4hour, daily, weekly, and (even less often) monthly charts. Without a clue of the larger
technical and/or inherent fundamental pictures, they are really just 'trading blind.'
Finding Sanity within the Chaos
What all of the previously mentioned translates to is an inferential conclusion where
technical indicators (at least those commonly used by the mass army of retail traders)
will provide false signals more often on shorter-term timeframes, over longer-term
counterparts. Simply put, retail traders who are taking positions on shorter-term
intraday timeframes (based on stock indicators), are actually making the situation
worse, and only adding to intraday volatility – even more. It's important to note retail
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traders are not the sole blame for volatility, as many institutions can also make silly
decisions as well. What's more, in today's trading environment, the historically
transparent environment of fundamentals (GDP growth, inflation, interest rates and
underlying economic reports) have many professional analysts scratching their heads
with the added variables of present and future national debt, credit related (out of the
blue) bombshells, inflation, deflation and risk aversion.
Thus, in the current Forex paradigm, the HIIV effect coupled with fundamental
uncertainty are creating the "perfect storm" for erratic intraday movements and HIIVderived volatility, contrary to traditional market-movement common sense.
When coming to terms with the fact that technical indicators are indeed failing in
today's markets, many readers may perhaps be wondering if there is any way to truly
put the odds back on their side?
The answer is yes. The solution is three-fold.
First, Retail traders can help remove uncertainty by spending more time attempting
to learn and understand the larger fundamental paradigm, while also trying to perceive
where future fundamentals will land. By doing so, retail traders are attempting to not
only decipher why present volatility exists fundamentally, but also map future
possibilities for seemingly unanticipated moves beyond today's price range.
Second, retail traders must also begin taking greater notice of institutional
indicators such as VWAP (and other benchmarks), understanding that institutional
order flow trumps all. Taking greater notice of VWAP (and other benchmarks) could
provide at-home traders with superior insights into the institutional mindset and thus,
potential future price action.
Third, retail traders must take the time to understand the philosophical and
theoretical underpinnings of volatility/probability, while also seeing how the
dynamics of markets demand the application of the principals of physics, helping put
the odds of success back in their favor. All three aforementioned points could be of
great benefit in helping defeat false technical signals, seemingly random price action,
and the lack of volume/order transparency retail traders are faced with daily.
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With everything we've covered in Chapter Two in mind, please make sure to
remember common technical indicators (especially on shorter-term timeframes) are
providing greater amounts of false signals, with each passing day.
It is arguable trading purely from technicals once allowed retail traders to clearly
see the fundamental paradigm unfolding via price action; however, within today's
Forex volatility, the bar for success has been moved much, much higher.
All participants must now pay attention to fundamentals, institutional-grade
technicals, volatility/probability, and market-physics to truly trade profitably in the
constantly changing markets of the 21st century…all of which we will cover in the
upcoming chapters.
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CHAPTER THREE
BEHIND THE CURTAIN
" Imagination can not only make people believe they have done
simple things that they have not done but can also lead people to
believe that they have experienced more complex events."5
- Elizabeth F. Loftus
In Chapter Two, we discovered how and why technicals are prompting false signals
in today's markets. Really, I would be very shocked to learn most readers were already
aware of the failure(s) happening, and had taken the time to identify specific instances
of such, while also really considering the 'philosophy behind' false signals in today's
markets.
When I discussing failing indicators at speaking engagements, or occasionally in
educational Webinars, I generally always ask how many people were aware of the
situation. Surprisingly, many will indicate they already had 'some notion' there was a
problem; however, virtually none have taken the time to investigate the matter more
deeply themselves.
Really, we've become so 'default dependant' that we often do not question what's
happening behind the curtain, even something inside of us is telling us we should. I'm
not just talking about indicators, I'm talking about the information we receive through
media daily too… I'm even talking about our own memories.
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Throughout Chapter Three, you're going to see some concrete evidence of why and
how our own memories fail us from time to time. In addition, we will also see how
and how some of the information received daily from media is not really telling us the
full truth. The two together are a deadly combination for investors and traders. To
transcend the modern paradigm of 'faulty information' potentially coming from inside
our own minds (propagated by external information and media), we must be willing to
look behind the curtain, always, even if we are part of the curtain, in and of, ourselves.
The Philosophy of Looking behind
the Curtain, Even if it's not
Socially Appropriate
Information and memory failure are not only subjects that keep me up at night, but
were part of the motivation behind releasing the information in this book, in the first
place. Over the past few years, it feels as if I am finding more and more evidence
showing that even if one intuitively feels the information they are receiving is faulted,
hardly anyone actually takes the time to investigate how and why the propaganda is
flawed.
I think it must be like having a tick embedded in one's back… One might know the
little bugger is present after having spotted it in the mirror after stepping out of the
shower. However, because the little thing is so hard to get to and because it's not
overly bothersome at that moment, he or she ignores it, hoping it will just go away. I
would think the host would ask another for help to remove the tick, which they cannot
reach with their own hands.
However, for many, actually asking another for help just seems awkward, perhaps
because for whatever reason, they're embarrassed that the tick is there in the first place.
Drawing attention to the annoyance just seems too uncomfortable to approach. Here's
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the thing though, 'the tick' could be carrying bacteria and every minute it is ignored,
the greater the probability the carrier could be infected with a malady like: Lyme
Disease.
Let me tell you what I know about Lyme disease…
Just a few weeks after I first moved to East Hampton (at the tip of Long Island) in
2008, I developed a funky little 'bulls-eye' rash on my shin. At the time, I didn't think
too much about it, as I figured it was likely just a funky bruise from biking, or
something. A few months later, I remember going to bed one evening feeling a little
strange, like I was just a 'more tired' than usual.
I didn't get out of bed for five days…
I had no idea what was happening. Fact is, I had no idea I'd been bitten in the first
place… Prior to moving to East Hampton, I'd never lived any place where Lyme
disease was a threat, and thus, had no idea to even be on the lookout for anything
peculiar, much less actually able to recognize possible symptoms. (Stay with me for a
moment and you will understand why this little story is so important to trading and
our perception of information.)
I finally pulled myself out of bed (feeling completely wrecked) determined to find a
doctor in my new hometown; however, I still didn't know what the problem was… I
remember thinking I must have caught a wicked strain of flu or something… While
searching for doctors online – and just by dumb luck really – I stumbled on a Webpage
detailing the symptoms of Lyme disease. After only a few minutes of reading, I was
convinced Lyme disease was the problem, and thus, I suddenly felt slightly better (at
least) having some insight into the catalyst behind my illness. Luckily, a great friend
was there to help find a doctor who could help and the next day I was treated with
antibiotics.
I caught the Lyme infection early and after only seven days of antibiotics, I was fine.
However, for those who aren't able to properly diagnose the condition, or ignore the
symptoms completely… The effects of Lyme disease (over the long haul) can be
devastating.
Often, doctors unfamiliar with the illness misdiagnose Lyme disease as Chronic
Fatigue Syndrome. Their patents are mistreated and eventually…end up feeling the
full force of the bacteria overtaking their bodies.
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The point behind all of this is very, very important. If you can't read the symptoms,
you can't diagnose the illness. The bull's-eye rash on my shin was a dead giveaway
that Lyme disease was present for anyone who'd seen one before, or if they had been
educated on such matters. In my case, however, I had never lived anywhere the
disease (or ticks) were present and had never been educated on symptoms or
preventative measures.
Fact is, because I didn't even have a clue of the possible danger lurking, even when
a symptom blatantly showed up on my own body.
Here's what's so important about this little story… The increased volatility of
today's markets is a symptom of unclear and misleading information, nervousness of
the investing public and troublesome economic and business conditions. In addition,
increased volatility within today's markets is also a symptom of a larger problem
whereby individuals, traders and even institutions are not able to clearly and
accurately find confidence in markets. Bad information is the bacteria in the
bloodstream. Also, remember in the close of Chapter Two, when I mentioned VWAP
(an indicator of institutional movement) as not readily available in most retail
platforms… Just another example of how the retail trader is not only missing vital
information, but perhaps not even aware the missing information exists at all.
I have to ask another question now, though it might seem a little odd…
On a personal level, is it possible your perception of markets is flawed, or even
worse…
Your own memory might be failing you right now, and you don't even know it?
Don't laugh… I'm serious, 'just what if?'
Do you believe most of what media delivers – news, polls and opinions – is/are true
and valid? What about financial news? Moreover, do you believe your memories of
past financial news and events are rock solid?
Chapter Three is geared to soften hardened and cynical hearts, while cracking open
the most riotous brains to the possible paradigm that we might all be snowed.
As competent adults, friends, husbands, wives, analysts, traders, executives and
market participants overall, we like to think of our minds as rational, with little error.
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What I'm talking about is personal confidence in our recollection and perception of
past, present and future reality. But what if…
What if some of the things we think we know as real, were never real in the first
place? How many of us could actually admit to ourselves (or others) that even though
we believe we are mentally adept, we were, and perhaps still are, wrong about our
own memories even.
I'm not just talking about trading psychology here, I'm also talking about human
psychology…
Perhaps what I'm about to show is part of the reason hardly anyone really knew the
financial crisis was coming. I know plenty of guys who currently tout 'they called it all
along' and 'they knew something was wrong way beforehand', but do not have any extra
zero's in their bank and/or trading accounts to actually prove it.
Yet, they all seem to have perfect 20/20 hindsight. Out of the thousands of
professional and retail traders I know – only one trader that I know of – placed a bet in
markets before the crisis started…
My friend Carl purchased index put options ahead of October of 2008, specifically
because he foresaw a greater problem stirring in markets, than most perceived.
I'll never forget the day in October 2008 when Carl called with news of his windfall.
He is the only trader I know of who actually took action on the information his
intuition was picking up on. All of the other traders, they're just kidding themselves.
They didn't see it coming ahead of time, or they would have made money, but that
won't stop them from telling you differently.
Now, I would like to give you an example of how the information we receive from
markets – and from ourselves – could be flawed. To do so, I must back up in time and
tell you about a market event – as it unfolded in my life…
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The Story of Black MONDAY - 1987
Do you remember the crash? I hate to admit this, but I was only in high school… I
do remember the crash though, because my father traded futures actively. One
afternoon when he picked me up from school, he seemed lost in thought. The day was
Monday, October 19, 1987 – the day the Dow Jones Industrial Average (DJIA) barfed
508 points, or 22.6%.
During the majority of my high school years, every Monday my old man would
pick me up after the final bell and we'd go have a burger and talk, you know, man to
man.
He'd then drop me back of at school for tennis, wrestling, or whatever other practice
I needed to make it to…
I have to say though, those Mondays sucked. I'm kidding really, as my old man is
gone now and I'd give a ton to have just one of those Monday's back…
Back then, however, I didn't feel quite the same. Every Monday, as the end of
classes would near; I'd consider finding a bus to throw myself under, just after the final
bell let out. See, the entire Monday ritual with my father was about more than just
having a burger and chatting; I was also required to hand over a piece of paper
containing all of my grades (I wasn't the best student); freshly signed by each of my
teachers. Every week, good old Mark got more than a burger; Mark received a welldone earful about his hideous grades, always in the middle of a restaurant.
October 19th, 1987 was very different from all the other Monday's though... On
Black Monday, My old man– the speculator, the stock operator, the futures trader and
the aerobatics pilot…never asked to see my grades. As we sat down to eat in the old
1950's Deco diner, he was studying one thing and one thing only: The Wall Street
Journal. But the paper wasn't fresh from a store, it looked well worked over, as he'd
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been writing on it all day. There were notes everywhere: calculations, ratios, lists,
letters and as I recall, even a few items circled with curse words scribbled to the side.
The burger joint was deserted, just enough, that I remember hearing the ceiling fans
rocking back and forth over the soft clamor of a mid-afternoon shift change in the
background.
Dave ordered a cup of coffee (black) from behind his paper; I ordered a Stewart's
root beer. Do you remember? The kind that comes in a bottle, with orange swirly
writing on the neck, stamped with '1924'.
My brew arrived with a straw and my old man's Jo, gorging in cream and sugar. I
remember him looking over the paper at me (I was waiting for the grade card demand),
down at his mug filled with cream and sugar, to the side, and then to our gumsmacking server, who was already on her way back to the kitchen. I'm not sure if he
smiled or sneered, but he drank the blunder anyway.
Silence was all I had with my burger that day, as I watched Dave's same dish toil in
abandon at the edge of the table. Silence –dead silence– like the kind where you're
cautious not to swallow too loud.
As I was eating, I unconsciously reached for my Stewart's. As I was siphoning the
last bit of soda, I accidentally made a huge schlurgle sound, the kind that only comes
from a straw. Normally, a schlurgle would not have been a big deal; today though, the
schlurgle was like dropping a piano in morgue…
Words cannot describe the
displeased look the gradeczar shot across the table just
after I'd broken his
concentration with my noisy
mouthful of root beer. I think
I made my first official trade
at that moment; I'm pretty
sure I was long and strong all
of the 'run for your life' calls
in the entire world.
Just at the moment I
thought Mr. Financial Paper
gawker-atter (and International king of staring contests) was about toss me and my
empty bottle of Stewart's all the way to Africa, he suddenly diverted his peepers over
my shoulder. Thankfully, the waitress had decided to check on his uneaten hammy.
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Saved by the forgotten burger; talk about a bull market! Before she could say anything
though, he'd already shook her off like a pitcher does a curve ball.
Then, unexpectedly, he called back after her…
"Get the hoodlum market-maker another stout, please would you."
"Whoa! Did Dave just order another Stewart's?" I recall my next
thought as, "this is a setup for sure… No doubt about it, I'm leaving in
a body bag."
"C'mere, I want to show you some things…" That's all he said while
the waitress was acquiring another bottle of suds… Even after he
ordered the second soda, I have to admit, I waited a few moments
before moving over to the chair next to him. My old man was a
great guy, but the second soda order was definitely out of place for
our Monday talks… Taking my new seat, I looked up just in time
to catch the waitress winking at my old man.
His face remained stone cold.
Then he began, "Today, you learn about life, money, fear, greed and
most of all…opportunity." Over the next few hours (and like six
more Stewart's!), he explained everything he possibly could about
Black Monday.
We talked about principals of psychology, markets, stocks,
trading, order flow, how market makers stopped picking up
phones, futures, derivatives, economics, common sense, mass herd
mentality, media Chicken Little, global money shifts, and most of
all…the thing he pounded into my head over and over…
"Mark," he looked directly into my eyes in a way that let me know I was about to
hear something very, very important, "today, Black Monday… It will come again in your
lifetime…once, maybe twice…"
He paused for a moment and then nodded in quiet kind of way with a content
smile, before turning back, "You'd better be looking for it, because it's going to happen –
eventually, and most people will be caught off guard."
Then he smiled again, "You should be able to make money on the way down, but if you
miss it – while most people are running scared from newspaper headlines, you should be looking
for some of the greatest opportunities to be presented in decades."
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In my entire life, I can't remember a more memorable afternoon than Black Monday
with my pop.
That afternoon, I think we both suddenly figured out that while I wasn't the most
punctual student, markets touched my soul in a way my classes never had. I don't
know why, but I just got it. That dark day of market devastation with my father, I
became a stock operator forever. I was born a speculator from the crash of 1987.
I can't remember everything my old man said that Monday, but I do vividly recall
him also speaking in terms of gravity, airplane engines, speed, aerodynamics, weather,
instruments… All in context of markets, but in terms I'd already come to know from
him– flying. The trader turned aerobatics pilot, my old man, my father, Dave, made
sure to present the information in concepts I'd already learned, to help it all sink in.
Occasionally, I wonder if 58 years beforehand, another young guy possibly made the same
mistake of loudly schlurping the last swig of root beer too…while in the company of his father,
recoiling from the aftermath of Black Tuesday, 1929.
Today, when I drink a root beer, I think of the crash of 1987 and how in an ironic
way, the historical global market plunge was really the conception of my life's path.
My old man died in his plane a few years after on July 4, Independence Day… That
might seem like a little more information than is required here, but it taught me
something else…
If you're going to love something, love it all the way, and never give up.
I sometimes wonder if my life would have taken another turn, if the crash of 1987
had never occurred. Maybe I'd just be shining shoes for a living now.
It doesn't really matter though, whether we're traders or shoe shiners, because
eventually a crash is going to catch us all…unless we can see it coming beforehand.
But to perceive the future… We have to be certain of the past…
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The CONFESSION of MASS MEMORY
FAILURE
There's a point to the entire story you just read…
Presenting a little insight into where I'm headed with all of the aforementioned
mumbo jumbo; we must all question not only the information we receive daily, but our
own memories as well. In short, while so many of us believe that our recollection of
historical events within our own lives is infallible, the empirical evidence on the table
could be saying something incredibly different.
Shortly after the turn of the present century, an article appeared in the UK Guardian
where writer Claire Cozens penned, "A group of US scientists has discovered that
advertising can alter people's childhood memories, making them remember events that never
happened."6
The above excerpt is specifically referring to the 2002 study by Kathryn A. Braun of
Harvard Business School, Rhiannon Ellis of University of Pittsburgh and Elizabeth F.
Loftus of University of Washington titled:
Make My Memory: How Advertising Campaigns Can Change Our Memories of
the Past.7
In the study, the authors assert:
"But times are changing, and some marketers are beginning to realize that memories are
constructive. Some have even benefited from the fact that their consumers' memories
have been manufactured. Take, for example, Stewart's root beer. They report many
adults seem to remember growing up drinking Stewart's frosty root beer in
bottles. This is impossible, because the company only began full-scale
distribution 10 years ago, and prior to that only fountain drinks were available.
It could be that glass bottles adorned with sayings like 'original' 'old-fashioned' and
'since 1924' provide consumers the illusion of a past that they might have shared as a
child. In fact, the vice president of Stewart's marketing swears he remembers drinking
their soda after Little League games in an area where distribution was unlikely, but
admits, 'Memories are always better when they're embellished' (Prince, 2000)."
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Fact is, I never drank Stewart's root beer in my childhood and neither did any
reader here, unless you specifically went to one of the Stewart's soda fountains, or
you're under the age of 19, as of 2009. 8
However, while all of the story about my father and Black Monday is absolutely
true (to the best of my memory), the fact that I really do seem to remember drinking
Stewart's root beer on the afternoon of the 1987 crash, shows that we are all fallible to
memory inconsistencies. Here's the thing, I would have likely gone through my entire
life thinking I was drinking Stewart's root beer in my childhood, had I not come across
Loftus' article in my research. Really, I had no reason to even question my own
memory, especially about such trivial things such as the type of soda I drank in my
childhood. However, now that Pandora's box is open, a little detail like a memory of
root beer brings up many, many larger questions.
I'm not talking about questions about the solidity of my memory, as I'm pretty sure
most of it is in pretty good shape; what I am discussing here is my 'little slip' of a minor
detail, when coupled with millions of forgotten 'minor details' by the mass investing
public, might really be a much larger problem. As I write this, I am truly wondering
how many readers believe they personally could never have any 'itty' inconsistencies
in their memories?
My direct question is this: I have admitted my memory is flawed, can you?
The thing is, until I stumbled on the research from Loftus, I would have never even
thought to question the memory I was holding in my own mind, as flawed… Much
like when I first noticed the little bulls-eye bruise on my shin, I no idea to even consider
the possibility of Lyme Disease…
Fact is, the greatest threats to our health, our success, our livelihood and our
longevity…often stem from events, happenings, understanding(s) and occurrences
inside of our own minds and bodies, which we are not aware of.
True, the tick was an external catalyst poisoning my body, however, the inability to
recognize the symptoms was a failure in my knowledge, mind and constitution in that I
had not even taken five seconds to consider the inherent dangers I should be cautious
of in my new surroundings… I can blame the tick forever, or I can take responsibility
for not having proactively sought out the tick, before the tick found me.
After I read the article by Loftus (and almost all of her downloadable work on the
University of Washington Website, which I highly recommend), I took the afternoon off and
simply went for a long walk. Though my mind (for whatever reason) still sees a
Stewart's root beer bottle in my hand almost twenty-two years ago, the evidence at
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hand has presented a different truth, which I absolutely must accept, even if by doing
so, I am admitting to myself that my own memory is sometimes flawed.
I can say with confidence that my memory of drinking root beer on the afternoon in
1987 is valid; however, I must admit that the detail of the brand is not. Interestingly, as
Loftus shows in her work, much of modern memory failure may actually be
propagated by advertising… What's more, her studies also show that memory failure
is not only real, but devastating to many who have been accused (and convicted) of a
major crime, even though they were truly innocent. (More on this in a moment…)
My next question to you is this: How can market participants trust their memories
of the trading and economic events from yesterday, if modern research is proving our
memories are highly capable of failing?
Would you believe memory failure is so plausible that real adults could even
misplace reminiscences of Mickey Mouse and Bugs Bunny? What about those who
'swear on the Bible' in Federal court?
Claire Cozens of the UK Guardian also wrote:
"Adults shown a mock advert in which Disney World
visitors shake hands with a Bugs Bunny character
became convinced they had done the same as a child.
But shaking hands with the famous cartoon character
could never have happened because the giant rabbit is a
Warner Bros creation and does not feature in any
Disney theme parks."
What I'm really trying to hammer home here is our
memories can deceive us… all of us.
Just when we thought we had 'steel traps' for
minds, another paradigm surfaces encouraging all of
us to question what we remember (and believe) in our
own minds.
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A date WITH Blind Devotion
You may have heard the cliché; Wall Street has a short memory… Well your damn
right it does and so do investors who keep coming back time-and-time-again to eat
poison apples from the same damn tree that put them in the hospital only a short while
ago.
Fact is, when markets begin to move (mortgage markets, dot com stocks,
commodities, the possible upcoming REIT penny stock surge, whatever…) the masses
seemingly perceive the potential to make a few bucks, and as momentum begets
momentum, suddenly become infected with (what I like to call) exuberance-inducedamnesia… Joey-Q-Public lines up one more time to take on the same reckless and
misinformed investments all over again.
Remember the Internet stock market dump at the turn of the present century? The
only difference between the dotcom.bomb and the recent mortgage crisis was instead
of owning paper, the same exuberant 'want rich, will buy blind-quick' mass investing
public rotated what was left of their wealth from ravaged tech stocks into houses.
The same investors went back for the same poisoned fruit (in a different wrapper),
thinking it couldn't possibly be venomous again.
But it was…
And it will be…
And they will go back for more, again and again and again…
Why?
Because their memories and deeper understanding of the situation are not only
synthetic and flawed, but manufactured from media, as well.
I seriously challenge you to ask your colleagues, family and friends what the
dotcom.bomb was all about?
I'd bet you will receive answers with sounds of 'artificially inflated' and/or
'overvalued Internet stocks', perhaps 'Enron', and most likely: 'daytraders'.
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On Wikipedia.com, there's a page titled Dot-com Bubble, which cites the main
reasons for the whole debacle as, "A combination of rapidly increasing stock prices,
individual speculation in stocks, and widely available venture capital created an exuberant
environment in which many of these businesses dismissed standard business models, focusing
on increasing market share at the expense of the bottom line."9
Please read the above explanation one more time, I'm going to point out something
huge in just a moment.
Moving on, please take a moment to read the first line of the paragraph following
the passage you just read: "The venture capitalists saw record-setting rises in stock
valuations of dot-com companies, and therefore moved faster and with less caution than usual,
choosing to mitigate the risk by starting many contenders and letting the market decide which
would succeed."
Here's what we have to understand. In the first statement, the only mention of JoeyQ-Public's personal responsibility is 'individual speculation in stocks'. Then, in the
second statement -the big explanation, the blame is clearly headed in one direction:
Venture capitalists.
Just like Stewart's root beer product placement influences memory and just like
pictures of Bugs Bunny at Disney Land influence memory, mainstream media always
finds an escape goat for tragic events in markets, which is/are the only things investors
really remember, after the fact. In essence, just like I can't remember clearly whether it
was Stewart's I was drinking on October 19, 1987, investors can't, don't, or don't want
to remember they were individually the ones who bought their dotbomb.com stocks in
an exuberant greed-fueled-feeding-frenzy. The bottom line is, because media
recollection of the event now directs blame at overzealous Internet entrepreneurs,
greedy venture capitalists and daytraders, most people have replaced their personal
responsibility and reality of the situation with the manufactured memories delivered
by Internet, television, print and radio. The 'product placement' here is that of 'shift the
blame', where investors forget he and/or she were (and are) responsible for their own
losses, by buying into the hype in the first place.
Why does this happen? Why is manufactured memory the accepted standard?
Foremost, information is everything.
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Take a moment to look at the larger outline of the Wikipedia article…
1
2
3
4
5
6
7
8
8.1
8.2
8.3
8.4
9
10
11
The growth of the bubble
Soaring stocks
Free spending
The "Bubble Bursts"
Aftermath
The Transition of the Bubbles
List of companies significant to the bubble
See also
Terminology
Media
Venture Capital
Economic Downturn
Further reading
References
External links
Little 8.2 'Media' is nothing more than three reference links at the END of the
article…
The links are:



e-Dreams
SatireWire
Startup.com
I don't want you to think I'm shifting blame here, because I'm absolutely not.
Individuals are solely responsible for their own investment decisions.
Period. However, based on the previously mentioned article, we can also assume
two critical points – one intuitively and one empirically:
1. Empirical – As Loftus' studies show, human memories are not only capable of
error, but are pregnable. (FYI, for those who are not yet believers, I will present even
more evidence in just a moment.)
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2. Intuitive - On the whole, people are lazy, greedy, move in herds, credulously
believe media, are addicted to exuberance, and frankly, never question anything unless
the same media actually tells them to question such.
I encourage you to look beyond my above Wikipedia cite regarding for a greater
dotcom.bomb explanation. Please Google the term. You will not likely find a
substantially wide variety of truthful explanations.
What's more, the register of explanatory articles is seemingly devoid of pieces
covering how media predominantly promoted, hyped, exaggerated, publicized fueled,
and inflated the whole Internet stock mess.
If historical coverage of the event seemingly absolves media from any responsibility
–as playing a major part in the catalyst of the Internet bubble, does that mean
mainstream financial (and non) media wasn't a huge part of the problem? Will the
masses forget the circuslike 'pitchman' role financial media played throughout the
whole event?
Perhaps they already have.
Speaking of memories, do you remember in Chapter One, when I mentioned the
50,000 watt mega-media-mouth bulb? Well here's the thing, Financial media is always
the first in line to promote any bubble whatsoever, because the bubble itself is
exuberance, and exuberance means ratings, and ratings mean advertising dollars.
Exuberance equals revenue for media.
What's more, when appearing on television, pundits are often told to ramp up the
tone of the discussion…
And because pundits want and need exposure they do. Here's an example, a VERY
real example, of how I know, from the inside… Just so you know though, I am not
going to mention the network's name, as I don't want to have to use all of the proceeds
from this book fighting a lawsuit. Nevertheless, here's what most people don't see…
Pundits are contacted by producers to appear on news and talk shows based on
expert status, producers exchanging information with one another, inside station 'go to'
lists and/or if the pundit happens to be in the middle of news, or has produced news
(like an article for a major financial Website) of notable mention.
Sometimes, the Producers will call the evening before to notify the Pundits that they
are invited to appear, though most often; the calls come in last minute just hours before
the slot. (By the way, usually there is no compensation for appearing on CNBC, FOX
Business, or various other networks, as an outside contributor, the trade is exposure for
time.) The producer briefs you on the subject you will be speaking on, sometimes
providing a little reading material, or questions; however, more often than not, the
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pundit is only aware of the subject and intended scope of discussion. And that's okay,
after all, pundits are supposed to be experts.
But here's what many might be surprised at… On more than one occasion, I have
actually been told to 'really speak out' and even 'argue fiercely'. What the average Joe
doesn't know (sitting front-side of the television), is this:
 Producers know what they want and they know who they can get it from.
 Pundits who do not play ball, do not come back.
 If you are told to argue, you argue.
 If you are told to be loud, you are loud.
I encourage you to watch the financial news with a fresh set of eyes. Are the
commentators and pundits seemingly excited and/or speaking above one's normal
'inside voice?' (Key network personalities generally do not have to play the same game
of fetch, just FYI)
Are there multiple participants in the studio, who seemingly 'debate' or almost
'argue' opinions, even though it seems like there's not much to argue about?
Do you think the elevated levels in their voices are purely because they are
passionate about markets?
Alternatively, is it possible the producer perhaps guided the 'energy level' of the
segment, or show beforehand? You better believe it.
Is yelling 'fire' in a crowded movie theatre effective?
 You better believe it.
 People move fast when they're fearful…or in the case of exuberance: hungry.
There are two problems with yelling fire though:
1. Unless you want to go to jail, you have to find someone to blame your outburst
on…
2. If you do get away with yelling 'fire' in a crowded theater (which you most likely
will, because it's dark and the patrons are paying attention to something else really),
if and when you do it again, you're going to have to yell even louder, because
you've already pulled the stunt once. The savvy stampede starter might switch up his
tactic to something like:
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'Look out! He's got a gun!'
Same thing, different wrapper.
(By the way, I'm not very good at manufacturing emotion – and thus, the networks don't
call very often anymore.)
In my research on the dotcom.bomb explanations easily available on the Internet,
there was one excellent article that came up on the #1 Google search page that deserves
significant mention…
The article was published on April 24, 2000 in New York Magazine; arguably not a
mainstream source of financial news. (Taking note of the article's date, the words were
penned in the heat of the moment and have a significantly different tone than
Wikipedia's reflection.)
The subheading of Michael Wolff's article Dot-Com Bomb reads:
"We've all been waiting for the next Great Web Wipeout. But the Orwellian
technology geeks never imagined the fuse would be lit by an old-media magazine
article."10
The first thought that comes to mind is, "Here's a guy who really get's it," meaning
our love affair with media-fueled exuberance.
Wolff asserts:
"Mania is always a pure play. It's reality confusion. It's blind devotion. It's a media
thing.
To me, the key constants of this manic phase have been the vast, astounding, messianic,
mesmerizing certainty on the part of technology-industry people on the West Coast
(together with their cursed, Orwellian language) side by side with the profound
insecurity on the part of the media that has reported the Internet story. While stupid
about technology, stupid about finance, stupid about the nature of the hype itself, these
people (we people) have been absolutely willing to believe."
Wolff's writing is just brilliant…
I believe he should be given a gold medal for the words:
"It's reality confusion. It's blind devotion."
At the heart of the issue, blind devotion means total and complete unquestioning
trust, completely forgetting the events of the past.
Forgetting the confusion created on the way up (and then on the way down as well), by
the same 50,000-watt-mega-fog-mouths' only a few hours, days, months, or years ago.
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What the 'mega-fog-mouths' will not do - ever - is publicly admit they were part of
the problem.
Wolff caps the statement with the words, "stupid about the nature of the hype itself,
these people (we people) have been absolutely willing to believe."
Dear readers, what will you remember about the financial crisis three months, six
months, and even five years from now? With so much information coming at you from
all angles (national debt, credit swaps, predatory lending, GDP loss, global tribulations,
asset nationalization, reckless spending, woefully high unemployment and foreclosure
rates), what will you really remember, especially when considering all of the
information you haven't even received yet… I can tell you one thing for certain; as
markets truly start to recover, who do you think the first 'pitchmen' to talk it up will
be? Yup...media. You will then be bombarded with a completely new suitcase of
information…and memories. In six months, nine months, or a year, will you really
remember the events in detail – other than retrospective mega-fog-mouth headlines?
If you do forget a year from now, fret not, I can guarantee you media will provide
you with a fresh serving of 'retrospective specials', just to jog your memory. Perhaps
help re-create your memory. Oops, did I just say that? I'm sorry, like media, I can't
remember what I just said, even though I just said it.
Let's focus on something else though…let's focus on you becoming a millionaire.
Let's focus on how much money you can make trading…
How much money you can make right now.
I mean right now.
I know three stocks, all under $5, that will triple in the next thirty days. Here they
are:
1. Nasdaq: IJCTSW – I Just Changed The Subject With…
2. NYSE: ESYWF – Exuberance, So You Would Forget
3. OTCBB: MPS – My Previous Statement.
Fear and exuberance are tactics commonly used to divert one's memory from five
seconds ago, to what could happen a few moments from now… Good financial writers
know it – effective media knows it…
I hope you do too.
Please take a moment to consider the following excerpts from two separate articles
by Elizabeth Loftus –
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In the 2003 article Our Changeable Memories: Legal and Practical Implications
(Nature Reviews: Neuroscience), Loftus states, "The history of the United States justice
system, like those of other countries, is littered with wrongful convictions made on the basis of
mistaken memories.11 Huff recently estimated that about 7,500 people arrested for serious
crimes were wrongly convicted in the United States in 1999. He further noted that the
rate is thought to be much lower in Great Britain, Canada, Australia, New Zealand and many
other nations, especially those that have established procedures for reviewing cases involving the
potential of wrongful conviction. "12
And also…
"The U.S. Department of Justice released a 1996 report after analyzing 28 cases of DNA
exonerations and concluding that 80 percent of these innocent people had been convicted
because of faulty eyewitness memory."13
The reason I've placed the above two quotes from Loftus in this book, is because I
want traders to understand that if people who are swearing on oath…in a court of law
are potentially falling victim to memory failure…
It IS plausible our recollection of similar technical signals, or market conditions that
may have surfaced two weeks ago…could be wrong. In addition, it is possible the
hyped (regurgitated and fresh) news we take in daily is altering our memory of the
past, and thus, our perceptions of the present…and future.
Given the massive ramifications of accusing someone of a crime while on the stand
(meaning an innocent person could go to jail for a long, long time), we can infer the
witness was either almost one hundred percent sure their memory was correct, had
some other type of mental, or psychological defect to allow such to occur.
Alternatively, perhaps somehow their memory was artificially altered… Aliens did it.
Just kidding. In reality, as Loftus research shows, the power of suggestion (in
recollection) can change what we remember about (and how we recall) past events.
On another note, media is often the 'psychological defect' witness I just mentioned,
in that media has no problem accusing anyone, and everyone, else to divert attention
from their own participation in the crime spree, metaphorically speaking.
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Investors who continually go for the same poisonous apples, repeatedly, either do
not know their memories have been impregnated, or sadly, cannot and/or will not find
the personal courage and strength stop the vicious cycle of blind devotion to media. In
essence, the acceptance of blind devotion is admittance to not only historically
believing in, but also having (consciously) allowed our memories to have been
manufactured by synthetic sources.
One would think nonchalantly believing in a hyped hot stock tip, or media touting
of an economic number intraday is one thing, however, recalling a false memory in a
court of law would likely see a much more serious 'other' requiring significantly greater
consideration and importance.
However, because it is proven human memories can fail in a court of law, where
there are potentially dire consequences, what does the evidence of such fallibility mean
about the plethora of less important information we're constantly receiving every day?
By the way, somewhere buried in this chapter is a good explanation for why I lose
my keys every three days…. Kidding…well…somewhat anyway.
Beyond the paradigm of our memories as fallible, there could be another 'add-on' to
the entire situation, making matters even worse…
What if the information we receive daily isn't even precisely correct in the first
place?
Given that we have just clarified there is indeed considerable possibility that our
memories can fall victim to 'manufactured recap' (based on media tributes, or revisits),
what are the chances of correctly analyzing history to make accurate decisions (today)
if the information was flawed from the start? Even more worrisome, what if almost no
one had any clue that information was flawed from day one?
There's just no way the masses – investors and media – could be that blind, is there?
If the information we have accepted as truth– suddenly presents another picture,
how many would honestly accept the reality of the new situation and how many
would actually attempt to justify the previously accepted untruth?
Part of the current volatility paradigm within markets is that of the public's mass
anxiety in reaction to events, propelled by media… Like all the quiet warnings of a
pending credit disaster –-prior to the fall of 2008, most investors and traders ignored
the possibility…until it became front-page news.
However, by then it was too late and those 'in the know' had already profited
and/or exited positions, precisely at the moment common investors were coming to
terms with the realization the apples they had eaten (again) were poisoned.
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Before we delve into the next section further examining 'how memory is
contaminated' I would like encourage all readers to take some time to explore Loftus'
work. Readers can find multiple articles and resources on memory failure, along with
links to Loftus' three books on her University of Washington Webpage.
For additional information, please visit:
http://faculty.washington.edu/eloftus/
I firmly believe Loftus' research is nothing less than 'game-changing' and I sincerely
hope she receives a Nobel Prize for her efforts, seriously.
Media Made Maladaptive Memory
Please take a moment to read the following statement by Loftus closely: "More
specifically, when people experience some actual event—say a crime or an accident—they often
later acquire new information about the event. This new information can contaminate the
memory."14
Let me ask you a few questions…
 Have you ever lost when trading?
 Have you ever watched as your portfolio freaked out in a global financial crisis?
 Have you ever seen the Dow Jones Industrial Average plummet from over 14,000 to
under 8,000 in a matter of months?
 Have you ever witnessed excessive volatility within Forex that either manifested, or
accelerated a loss?
If you are an active trader, you likely answered yes to all of the above questions. I
would like to present the possibility that after-the-fact 'manufactured memory' often
plays a significant role in many traders' ability to adapt to, evolve with, and overcome
volatility, when markets change paradigms. In essence, the average trader's (and mass
public's) inability to rapidly adjust to continually shifting market conditions is derived
from two sources:
1. Maladaptive fear and blind devotion.
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2. Lack of knowledge and experience.
For the duration of Chapter 3, we're only going to focus on #1 above, maladaptive fear
and blind devotion.
(The totality of Volatility Illuminated is geared to help overcome #2.)
For those who are not familiar, 'maladaptive fear' is a type of unnecessary, manmade
bad fear, which is often harmful in our lives. On the other hand, 'good fear' is known
as adaptive fear. Again, 'bad fear' is termed maladaptive fear.
As a working definition, "Adaptive fear is a nuanced emotion that diminishes during
times of relative safety, while maladaptive fear lurks beneath the surface all the time, quick to
make its presence known whenever there is discomfort, the unknown, or change."15
Maladaptive fear is really the product of a traumatizing circumstance, where after a
devastating event has taken place in our lives, when faced with a similar situation (or
possibility of), our brains and bodies manufacture the symptoms of biological fear,
even though nothing is truly 'to be feared' at all.
In the book, Injuries in Athletics: Causes and Consequences author Semyon
Slobounov states, "fear is one of the major components of psychological trauma that may or
may not develop as a result of traumatic injury."
The importance of the previous statement rests within the words, "as a result of."
Maladaptive fear or conditioned fear is a byproduct of an event that can literally alter
our brain chemistry to react to future events. Again, bad fear is separate from adaptive
or healthy fear, in that when we are feeling adaptive fear, we are (literally) usually faced
with physical peril.
Specifically, according to Rosen & Schulkin (1998) "Fear responses (e.g., freezing,
alarm, heart rate and blood pressure changes, and increased vigilance) are functionally adaptive
behavioral and perceptual responses elicited during danger to facilitate appropriate defensive
responses that can reduce danger or injury (e.g., escape and avoidance).
However, pathologic anxiety, as a form of an exaggerated fear state, may develop from
adaptive fear states as well. If that happens, the hyperexcitability of fear circuits that include
several brain structures…"16
I cut off the sentence a little there, as the passage delves into brain chemistry
terminology (if you'd like to continue reading, please see the endnote); the point is that
beyond our normal 'healthy fear' levels, constant upsurges of the adaptive fear state
can mutate into maladaptive fear, where we begin to feel anxiety and fear (constantly)
even when we really don't have anything to truly fear at all.
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Do you think media plays a significant role in pushing the greater public into a state
of maladaptive fear?
You should – but you should also know media does the same with 'maladaptive
exuberance' too.
In essence, a maladaptive state is where we perceive current events as correlated, or
will possibly have the same outcome as previous – traumatizing – events, even though
the current event is completely independent from the previous event.
But maladaptive fear cannot exist without first having a trauma take place…
In the case of media, the trauma does not always have to come in the form of
'instant shock', like 9/11 (every single person I know (including myself) was literally glued to
the tube) or the financial crisis, as a slightly duller example. However, the trauma can be
a slow, grinding campaign of fear, or exuberance propaganda.
Why do you think the evening news is filled with so much negative crap? Because
as a society we not only buy into it big time, but also have become addicted to needing
to know the negative crap, so we're not blindsided by trauma.
But the trauma is the slow creation and conditioning of maladaptive fear by the
daily negativity and fear grinding. If you're always worried about something, you're
likely trusting of the anyone has an 'in' to information, or news that helps alleviate
your anxiety, or make you feel safe, by presenting you with more information about
negative information.
Case in point: I've randomly pulled two screenshots from major news Websites …
(I've left their names out as I try to avoid a lawsuit for the second time in this book.)
Again, I did NOT search for the news, I simply hit two major websites as I was
writing these words and snapped the screens with no doctoring, or digging to
manufacture evidence. The point, as you will notice on the following page, 70 to 90
percent of the information we're being fed by media today, is fear based wretchedness.
However, the same fear peddlers will likely change their campaigns into exuberancebased wretchedness, just after enough of the fear junk has been deployed so that the
public is well conditioned into a reasonably stable state of constant anxiety…
(By the way, I pulled the two following images only minutes apart – from different
continents – to show fear-media isn't just American, it's global.)
In the first example from a major European publication, nine of the 11 headlines are
CLEARLY negative…
That's 81% negativity in terms of the information delivered at the moment the
screenshot was taken.
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(I grabbed the headlines on May 27, 2009 – just FYI)
It's amazing…scary…and devastating to see the maladaptive anxiety conditioning
paradigm in action.
Figure 3.4
Figure 3.5
The above major U.S. publication is slightly better in the fear department; however,
65% of the headlines are still negative.
All of this leads us to Media Made Maladaptive Memory (MMMM)
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Media Made Maladaptive Memory is created through the conditioned acceptance
of hype, negativity and/or whatever else we are being pitched at every moment by
media that is seemingly imperative to our immediate protection or well-being, but is
really doing nothing more than creating un-necessary anxiety.
(By the way false Media Made Maladaptive Memory is not a professional term, it is my
term, which I made up to try to explain the entire paradigm in greater detail. I'm only telling
you, because I hope to be a part of the solution, not a cog in the larger problem and I don't want
you to think I'm citing a professional psychology term, when I'm not.)
Here's what I'm saying though: mainstream 'modern' media is possibly creating
maladaptive fear (and anxiety) within the masses, who are constantly begrudged with
fright, panic and dread through televisions, the Internet, radio and newspapers.
I ask, is the constant bombardment of negative, or almost synthetically positive
(exuberant) headlines a form of intimidation in and of itself? I thought public
intimidation was illegal, though perhaps I'm wrong.
I seem to remember reading something about civil rights somewhere… Perhaps it
was Title 18 of the U.S. Code Section 241, Conspiracy Against Rights, that said
something like, "This statute makes it unlawful for two or more persons to conspire to injure,
oppress, threaten, or intimidate any person of any state, territory or district in the free exercise
or enjoyment of any right or privilege secured to him/her by the Constitution or the laws of the
United States, (or because of his/her having exercised the same)."17
Honestly though, I can't remember exactly what it said…
Merriam-Webster dictionary defines intimidation: "intimidate, cow, bulldoze, bully,
browbeat mean to frighten into submission."18
Here's what I'm not doing: Insinuating whatsoever that media is breaking any laws,
after all, this is America and media has the right to free speech, just like everyone else.
When we see 65 percent and 80 percent of headlines touting negativity though, we
might want to at least (personally) take notice that there's a type of 'influence' taking
place.
If the news just reported news, like non-trivial whatever, would you be interested?
The flaw in the human condition is that we are drawn to sensationalism, whether it is
fear, or exuberance. The critical point of understanding here as well, is that
intimidation isn't always in the form of negative headlines. Remember my previous
discussion on the dotcom.bomb?
Well, if you were trading prior to the turn of the century, you likely remember terms
like "new economy."
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Mainstream media was all over 'new economy' mania touting rising indexes and
rocketing stocks, while Internet companies poured in the advertising dollars… In
January of 2000, sixteen dotcom companies forked over (on average) $2.2 million each
for 30-seconds of fame during Superbowl XXXIV. 19
Momentum begets momentum and nothing attracts a crowd, like a crowd.
The problem is not only are our memories 'influenced' by whatever negative, or
positive hype is taking place in the moment, however, the controlling emotion of the
present is actually the catalyst helping to keep the 'extreme anxiety' helix in motion…
See, while in the thick of exuberance, media is your best friend, all the inside scoops,
stories and tips… The pitchmen are all too happy to sell the greatest show on earth,
and dear friend…the trend will never end…
I don't care if it's Internet stocks or real estate; all trends do eventually end.
Case in point, the last three letters of trend are:
end
When the bubble bursts, your old media pal (who was peddling tickets to the show
the whole way up), will immediately puke out the words: I told you so.
And as quick as lickety-split, hawker-media will turn tides, being the first to change
face and tell the crowd, 'it was that dirty old rich fatso Ringmaster.' The same mediamouth that was selling the tickets to the circus-leader's show (only moments ago) will
suddenly become 'a vigilante of the people', asserting that it's imperative to take down
the portly 'Richie Rich' who did you wrong.
Someone, somewhere, always swindled the public; never the public or media
themselves. During the Internet era, it was highflying entrepreneurs and venture
capitalists; individuals had nothing to do with the stocks they personally bought while
riding high atop fluffy greed clouds. In the current crisis, individuals were duped by
predatory lenders, with the larger criminals being credit-swap traders and investment
banks… All those people who bought too much house, just because 'they could', had
nothing to do with it.
Fact is, in the first moments of any bubble bursting, media will immediately find the
biggest scapegoats it possibly can (as quickly as possible) immediately, diverting the
public's memory from the ham-bread hype Mr. Internet and television were handed
out, all the way up. Then, as the bubble draws out, media drowns the masses in
negativity… After all, idol minds are the devil's workshop and an idol mind, might
begin to remember that media had almost as much to do with the 'irrational
exuberance' of the bubble, as those they are currently hanging.
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The conditioned maladaptive fear shtick works perfectly and just as the crash
rounds out of the bottom (and as quickly as Jekyll turns to Hyde); those swell old
media mouths and pundits are back on the bull bandwagon again, circus exuberance in
hand…
Old 'mega-mouth' might even mention he's learned his lesson and this time, he can
help you spot the poison apples.
The evidence shows (repeatedly) the deflection of blame for crashes and bubbles,
coupled with the constant cyclical maladaptive fear and exuberance conditioning
ensures no witnesses will remember the truth from the scene of the crime…
What's more, the 'confusion' of blind devotion is an ongoing game that must be
continued daily, even when there is no apparent 'fear' and/or 'exuberance'.
And as you're about to see, even the 'accepted standard' of statistical information
regularly delivered to masses is part of the larger 'confusion' puzzle keeping the
investing masses from ever seeing the truth clearly.
The Accepted Standard of
Nothingness
It's blind devotion really, to take in information and never question how the
information is compiled… Reflecting back on the same Loftus' quote from the opening
of this chapter:
"Imagination can not only make people believe they have done simple things that they have
not done but can also lead people to believe that they have experienced more complex events."20
When the EUR/USD plummets 300-PIPs intraday (after the release of a
consumer sentiment survey), retail traders who were caught going the wrong way can
easily fall precisely into the aforementioned trapping.
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See, the 'event' was the loss. Was the cause the consumer sentiment report? Not
really, the true cause was the breakdown in the way information is collected and
delivered. The subsequent event to the sentiment report, which preceded the market
move, was sell side traders firing out orders because the market was moving away
from their benchmark. (I know this sounds a little foreign right now, but by the end of
Chapter Eleven, it will likely all come clear. The larger explanation of the motivations
behind institutional buying and selling demands a thorough explanation, which we
will get to in Part Two of Volatility Illuminated.)
IMPORTANT NOTE:
Over the following pages, you are about to read how one commonly coveted 'economic
indicator' is slightly flawed… Let me rephrase that… The report is not flawed in
itself, in actuality, it is calculated exactly as the 'industry standard' says it should be.
However, the 'industry standard' in itself, is slightly misleading and probably needs
to be reconsidered. Again, I am not saying the report, or the organization, is
misleading the public, nor am I attempting to pick a fight with the organization. I am
merely speaking to the accepted standard of gathering, analyzing and deploying
information to the public. It may be possible that 'polling data' within media
(including politics) might need a little reshaping to help deliver a more accurate
picture to the public.
Let's take a moment to talk about the scope and accuracy of the fundamental data
we receive in markets.
According to the Philadelphia Fed, the University of Michigan Consumer Sentiment
Survey is:21
Consumer confidence surveys measure individual households' level of confidence in the
economy's performance.
The monthly Survey of Consumers is a nationally representative survey based on
approximately 500 telephone interviews with adult men and women living in households in
the co-terminous United States (48 states plus the District of Columbia). For each monthly
sample, an independent cross-section sample of households is drawn. The respondents
chosen in this drawing are then re-interviewed six months later.
A rotating panel design results, and the total sample for any one survey is normally made up
of 60 percent new respondents and 40 percent being interviewed for the second time.
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The Index of Consumer Sentiment (ICS) is derived from the following five
questions:*
1. We are interested in how people are getting along financially these days. Would
you say that you (and your family living there) are better off or worse off financially
than you were a year ago?
2. Now looking ahead--do you think that a year from now you (and your family
living there) will be better off financially or worse off, or just about the same as now?
3. Now turning to business conditions in the country as a whole--do you think that
during the next 12 months we'll have good times financially, or bad times, or what?
4. Looking ahead, which would you say is more likely--that in the country as a
whole we'll have continuous good times during the next five years or so, or that we
will have periods of widespread unemployment or depression, or what?
5. About the big things people buy for their homes--such as furniture, a refrigerator,
stove, television, and things like that. Generally speaking, do you think now is a good
or bad time for people to buy major household items?
Okay, so now, let's go back to the basics; reviewing lecture notes from "Introduction
to Statistics," by Steve Stanislav of North Carolina State University, it appears there are
really three types of sampling that apply to this type of data collection:22
1. Simple Random Sample (SRS) of size 'n' consists of n individuals from the
population chosen in such a way that every set of n individuals has an equal chance of
being selected and each sample has an equal chance of being selected.
Note: A SRS does not allow for favoritism by samples nor self-selection by
respondents
2. Stratified Random Sample - to select a stratified random sample, you must first
divide the population into groups of similar individuals called strata/stratum. Then
choose a separate SRS in each stratum and combine to form the full sample.
3. Multistage Sample - same concept as a stratified random sample but you divide
each strata even further. So random samples eliminates bias, but when a population
consists of humans (as it does on earth), accurate information requires more than 'a
good sampling design.'
Hold your thoughts on the sampling space for just a moment, let's take a look at the
"surety" behind the numbers we are receiving from the media in the first place…
There are two factors go into figuring out how "confident" one can be that an entire
population feels one way, or another: The confidence interval and the confidence level.
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Starting with the confidence interval, which according to Creative Research Systems
is, "the plus-or-minus figure usually reported in newspaper or television opinion poll
results." For example, if you use a confidence interval of 4 and 47% percent of your
sample picks a particular answer, you can be "sure" that if you had asked the question
of the entire relevant population…between 43% (47-4) and 51% (47+4) would have
picked that answer."23
The second factor is the confidence level, which according to Creative Research
Systems "tells you how sure you can be. It is expressed as a percentage and represents how
often the true percentage of the population who would pick an answer that lies within the
confidence interval. The 95% confidence level means you can be 95% certain; the 99%
confidence level means you can be 99% certain. Most researchers use the 95% confidence level."
So let's say that you live somewhere like, well let's just say: the United States. In the
North American country, there happens to be 305,705,463 people, as of the spring of
2009. If you wanted to report (with accuracy) how confident a statistical study
could/would be that 95% of the population felt a particular way, you would first find
the "confidence interval," which we just covered. However, let's drill into the number a
little, just to see if there's anything we might find interesting… If we input the
expected confidence level of 95%, with a population size of 500… attempting to
calculate how about half of the people felt on one matter, or another, our confidence
interval would be 4.38. What this means is that if you survey 500 people in America on
a subject, you can be 95% sure that between 45.6% and 54.4% of the people would
agree.
Funny thing though, if you wanted to be 95% sure that between 78% and 82% of the
people in America agreed with your answer, you would need a sample size of 1,537
(the confidence interval would be 2, FYI.)
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TO SEE VOLATILITY ILLUMINATED YOU
MUST BE WILLING TO
SEE INFORMATION CLEARLY
Okay so here's the deal… The commonly accepted methodology behind the way
major polling data is collected is drastically faulted, though it's not the University of
Michigan's fault. It's about 'media protocol' delivering partial truth to the masses. Part
of the issue is that of the good old "media business as usual", which propagates
misinformation to the public.
Really, what I'm getting at, is that given the population's size, we can be 95% sure
that about 50% of the people in America agree with the survey's results.
I don't want to bash the University of Michigan here, because it's a general rule of
thumb that when sampling a population for statistical results presented to media; one
needs to use the 50% benchmark to assume a worst case scenario.
Then again, the media doesn't really tell you this little detail when most surveys are
released, do they? Honestly, I couldn't even find the information on Reuter's site.
What I'm really saying is that what we have is a two part problem. To pad for error,
researchers are forced to use "worst case" confidence levels, which in turn means
smaller sample sizes. Making matters even more unnerving, when the results are
published, consumers are not informed of the data or confidence levels used behind the
information they are receiving.
Take the last sentence in the first paragraph on the December 2008 report, which
read, "Although most consumers view the recent price declines as due to the recessionary
downturn in spending, even longer term inflation expectations have decreased. While most
consumers expect a rebound in prices when the economy recovers, they now anticipate a
somewhat lower overall inflation rate to prevail in the future."
Here's the point, according to The Study of Economics: Principles, Concepts &
Applications, published by McGraw-Hill:24
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"The most common cause of inflation is too much money chasing too few goods. If
everybody had 5 times as much money, but the amount of goods and services
produced remained the same, prices would naturally rise by a factor of five. So the
answer to avoiding inflation is simply to avoid printing too much money. Easier said
than done…
Government leaders like to spend a lot of money on military equipment, roads,
subsidies, building projects, etc., because this keeps them popular with their
constituents. But getting money to pay for these things is often difficult. Raising taxes is
as unpopular as government spending is popular."
So my gripe with the information provided three paragraphs above from the
December University of Michigan Consumer Sentiment Report is this: How can "most
consumers" believe "a somewhat lower overall inflation rate to prevail in the future,"
when it's economics 101 common sense that when the Government prints more money
(think stimulus and bailout), inflation becomes a deadly threat looming?
Who are these "most Americans" anyway?
Either "most American's aren't aware of the real situation at hand – meaning the
survey is a contrarian indicator – or we're not getting the real story.
Listen to this…first, sure, yea right…it makes sense that many American's wouldn't
feel like 'too much money was chasing too few goods', after all, almost none of the cash
the Government is handing out is showing up on the average American's doorstep. For
the little guy (the retail trader) the only real stimulus he's getting is a headache with the
slow economic grind down, while watching executives blow hordes of bailout cash on
leer jets.
Case in point, by June of 2009, weekly Federal Reserve Data indicated core loans
and leases from banks were down almost 8% over the previous three months, and 1.6%
over the year ago period.25 The facts clearly show consumers have not been the
benefactors of Government spending, even though (in all) US Government recovery
spending was nearing almost $3.8 trillion (Federal Reserve, Treasury, Federal Deposit
Insurance Corporation, Federal Housing Administration, Congress and Joint Fed, FDIC
and Treasury) into the early summer of 2009. Well you're darn right many consumers
aren't aware to be on the lookout for inflation, after all, they hadn't/haven't –
personally, seen a nickel of the Government's monetary upchuck since the start of the
crisis.26
There's something else happening here too; remember those confidence level
things? We're talking about basing opinions on whether a 'slight majority' of the public
feels conditions are getting better, or worse. But what is 'slight majority' data anyway?
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Want to know? I'll tell ya…'slight majority' data is just the type that's required to
determine the outcome of an election…like if you get 51% of the votes, you win.
However, economics do not work that way...if 54% of consumers vote the economy is
improving, a larger economic 'growth cycle' doesn't just 'win.'
And yet; similar methodology is used in polling for economic sentiment, as
Presidential elections. Uh… Okay…
At the end of the day, it is important to take all "survey related" reports with a grain
of salt. In addition, when we dig into the information delivered by media, in many,
many cases we find the information is often 'murky'… I'm not saying the media is
fibbing, what I'm implying is the information delivered does not truly and accurately
lay out the entire picture from an unbiased, or impartial standpoint.
What's more, mainstream media tends to have a heyday with "consumer sentiment"
reports, which is really a translation of a translation, making big inferences about the
total population, which in part, is just another shoveling of nothingness into the
individual's lap. What we're talking about is light-speed information changing the
total critical mass of market moving disasters pending… Oh, wait, what I've just
mentioned doesn't come until Part Two of Volatility Illuminated. 
At the end of the day, what I'm really proposing here is that much of the
information often 'reported' to the public (regarding fundamentals) isn't really fully
explained and thus, it's no wonder the average investor always seems to get the shaft
every few years…
Unfortunately, we simply cannot depend on mass media to deliver clear, helpful,
reliable information for our investing pursuits…we MUST (as individuals) take the
time to truly dissect ALL of the information that could have any impact on the
positions we are taking within whatever market we are trading… Sounds like a ton of
work right?
Right, which is why 95% of all retail traders lose.
What I'm saying is 'man up' and dig into the details.
Overall, the larger point behind everything you have just read is… Not only is
much of the information we are receiving potentially faulted in delivery, but because
we are receiving potentially misguiding information from the start, our memories
could be hindered in the future, when attempting remember the past.
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What we have is a massive problem with the clarity and delivery of information
overall, where the individual must take the time to not only understand the
information coming forward, but also reflecting upon how major media is reacting to,
and then delivering, as well.
Media has a major interest in every headline delivered... What I'm talking about is:
the more you staying glued to the tube, the more the tube keeps advertising revenue glued to the
network's wallet.
Thus, we have to not only keep a close guard on our emotions, as we take in
everyday information, but we must also understand that the constant bombardment of
positive or negative headlines is affecting our memories. What's more, when the
information of today is repackaged and redelivered in the future, as a historical recap
of what was happening today; if we did not take the time to accurately understand the
events unfolding now, we will not remember correctly in the future, and thus, could
fall victim to having our memories partially recreated in tomorrow-land...
Referencing the famous line by Gordon Gekko, Michael Douglas' character in the
movie Wall Street, it's probably a good idea to second guess almost all of the
information surfacing from media, as with slightly closer examination of the facts, we
could find 'mega-fog-mouth' actually just slapped some lipstick on a pig…
Now that we've covered why and how we must question almost all information we
receive daily, we will now talk about two technical strategies that generally work well
within in trading.
However, we will also attempt to understand why the technical strategies can also
fail at times, thus leading us into a greater understanding of why volatility and
probability and understanding institutional order flow are necessary to (at the very
least) double check the technical indicators most view as reliable…daily.
As one final side note, I don't want readers to think I'm insinuating we have
'question everything', like as in we should walk around in a paranoid state of distrust…
Please do not mistake my point… What I'm really saying is…common sense sure goes
a long ways… That's all really… just plain old-fashioned common sense.
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CHAPTER FOUR
FIBONACCI & Pitchforks
Forex markets are tricky, there's no doubt about it. Wide spreads, seemingly
unexpected volatility and odd hours can all take a huge dent out of traders' wallets.
However, with a few simple strategies, both long and short-term traders can
potentially make a big difference in their bottom lines. Here we're going to cover two
simple trading strategies: Fibonacci Retracements and trend analysis through
pitchforks. What's more, we will also overlay the two strategies, creating what we will
call the Forex Fibonacci Pitchfork Strategy. By utilizing Pitchforks and Fibonacci
Retracements in our trading, we may find ourselves suddenly empowered with what is
really… an almost laughably simple (but effective!) trading tool.
Getting straight to the meat, Fibonacci Retracements are probability points where a
currency or stock are 'expected' to bounce back near, after a large move, before
continuing in the original direction.
Think of Retracements in terms of Newton's Third Law of Motion: "For every action
there is an equal and opposite reaction."
Within this understanding, trading carries some of the same principals. However, I
would like to add that after a large move, the opposite reaction can quite often lose
energy quickly, and thus, is why the 'reactive move' after a larger previous ascent, or
decent, can be less than the large move itself. This is not to say that once a large upside
pop, or landslide selloff takes place, the currency will not completely retrace the
original move, however, without a fundamental event prompting a larger reversal,
energy is often lost in the bounce.
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Employing Fibonacci Retracements, we can find some guidance as to where the
reactive-moves could lose steam and continue in the original direction.
Ironically, Leonardo Fibonacci lived in the 13th century, while Newton worked in
the 17th century. Perhaps Fibonacci unknowingly uncovered the truths behind the
laws of motion…centuries before Newton's name became a name brand of motion
postulation…
Fibonacci in Nature
If you're not familiar with Fibonacci ratios /numbers, the concepts of such are
directly consequential from nature, and are found in virtually all organic sciences
today. Briefly, a Fibonacci string results from adding previous numbers together, to
find the next. For example 1+1=2, 2+1=3, 3+2=5, 5+3=8 and so on… The Fibonacci
string would look like: 0,1,1,2,3,5,8,13,21,34,55,89,144,233...
In nature, the spiral of seeds in a sunflower are exactly ordered in Fibonacci
sequence, as with many occurrences in organic life.
Fibonacci ratios are thus, derived from organic numerical sequences. For example,
if you take any eighth number in the sequence and divide it by the number following it
in the sequence (dividing the eight by the ninth); the answer will ALWAYS be 61.8. In
the above string, if we divide the eighth number (21) by the ninth (34), we get 61.76, or
61.8 rounded up.
It just is.
Market quants hold that Fibonacci is not only true in organic matter, but also carry
substance within day-to-day trading as well. Thus, Fibonacci ratios often lay out of a
map for Retracement levels, after a significant move.
However, because bounces must put in lower lows, or higher highs for a larger
trend to remain intact, we intuitively also understand Fibonacci ratios only hold true,
so long as a trend is indeed...in effect.
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Thus, perhaps Newton's Law of Motion that says, "For every action there is an equal
and opposite reaction" fails to take into account the loss of energy in reaction, when
markets are trending.
There could be another factor involved though, which may be overcome by
combining Fibonacci with the founder of quantum physics Max Karl Ernst Ludwig
Planck's formula E=hv, where "energy is and absorbed in quantities divisible by
discrete 'energy elements'".27
For the physicists out there, don't worry, there's plenty of goodies for you in
following pages. Now, let's look into how one can very simply use Fibonacci
Retracements in Forex trading, without any complicated math.
The Fibonacci Prophecy
All of the magical math in the world will never make Fibonacci Retracements true
100% of the time. Period. Thus, a little common sense goes a long way when using any
type of mathematical or technical indicator to trade with. If the market is showing
something different from the indicator, enough people believe in something different
from what the indicator is presenting, and thus, the indicator is wrong. Fibonacci
Retracements are relevant only so long as enough people are watching and acting on
the same information that the "collective whole" makes the occurrence a self-fulfilling
prophecy. In other words, even if you've opened a trade based on Fibonacci
Retracement expectations, be prepared to close the position, should common sense
warrant such. In addition, as I've just mentioned that Fibonacci Ratios/Retracements
require some application of a self fulfilling prophecy, too many people acting on the
same information at the same time, can actually cause excessive volatility, as noted in
Chapter Two.
Fibonacci Retracements work on both short and long-term periods, for all types of
traders. For this chapter though, we will only look at Fibonacci Retracements for shortterm trading on 4-hour charts.
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First, before we even consider using Fibonacci Retracements, we need to be able to
spot when a move has occurred that would warrant using Fibonacci Retracements in
the first place. This can be as simple as looking at a chart, and visually identifying
when a large move has transpired, and/or capitulated.
What I mean by this is, when looking at a chart, if you're expecting to see empirical
proof that a move has stalled, you will never be able to do so. You will see some signs,
like CCI turning upward from -100 (and vice versa downward from +100) or
Stochastics bottoming out, or a candlestick pattern like a hammer bottom, but you will
never know absolutely 100 percent for sure. If there were some way to know all the
time, everyone in the world would be rich. One way to have a slight bit of assurance
though, is to read volatility compression through short-term volatility bands
compressing back underneath long-term volatility. The aforementioned is likely
foreign sounding to most, as it should be. I will explain concepts of volatility bands in
detail, in the second half of the book. For now, simply log the statement in your mind,
for future reference.
Traders can learn to intuitively 'feel' when a move has capitulated though.
However, only countless hours of pouring over charts will give you 'the feel'. Once
you are able to infer a move is over though, you can begin to apply Fibonacci
Retracements for trend re-entries, or profit targets points, if you are trying to trade the
rebound.
I would like to mention that attempting to trade a 'bounce' is risky business and is
not really the subject matter of this book. However, we will look at a possible reversal
trade with Fibonacci Retracements, just to cover all our bases. Really though, when we
use Fibonacci Retracements, we should use the technical tool to time our 'trend reentry' points in an attempt to take positions with the trend, not against.
Looking into when to apply Fibonacci, the below chart shows a significant
downward in the USD/CHF (U.S. Dollar / Swiss Franc). What we see is a 'significant
move', which is precisely what we're attempting to find when applying Fibonacci
Retracements.
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Figure 4.1
Based on Figure 4.1, many traders were likely looking for additional downside to
come, as the USD/CHF previously took out support in the 1.0950 area. A major breach
of support or resistance is often a key signal that more trending is to come.
Some turned the dollar long, others waited for key Retracement levels to be hit,
before taking positions…
The bottom line though is we must be able to identify some sort of 'significant
move', before we can apply Fibonacci Ratios at all.
With the aforementioned in mind, we will now take a look at how we can use
Fibonacci Retracements to trade a possible 'bounce' or reversal, once a larger move has
taken place.
In Figure 4.2, you will see a large downward move, where the Australian dollar
declined significantly against the New Zealand dollar.
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Figure 4.2
Several indicators (not shown) were prompting the bulk of the damage was done
and the pair would likely experience a 'bounce', otherwise known as a short-term
reversal.
Regardless, the Retracements can also serve as profit targets for reversal trades.
Perceptive traders could have taken long positions in the Australian dollar, off the
bottom of the range, using the low of the range as a stop.
By means of Fibonacci Retracement levels in such a case, traders would use the key
indicator as possible profit targeting points. If one had taken a position in the
AUD/NZD off lows, when the pair tagged the 38.2% Fibonacci Retracement level, it
would have been a good idea to either take all profit, or place a stop slightly below the
38.3% Retracement. The reason for placing a stop just below the 38.2% Retracement is
this:
If the bounce is real and a reversal is truly in effect, chances are the upside momentum will
persist, however, as Fibonacci Retracements are significant trend re-entry points, and given that
positions into retracements are moving again the larger trend at hand, locking in bounce profits
is always a good idea.
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Again, Fibonacci Retracements are also key levels where 'with the trend' traders will
begin wading back into a pair… What I mean by this is if a Forex pair, or stock, just
witnessed a massive downside slide, many traders are likely trying to find low-risk
short entry points to capitalize on another move downward, should more selling
surface. Thus, the 'bounce' trader will experience significant volatility at key
Retracement levels, as many 'with the trend' traders attempt to take opposite positions.
Thus, bounce trader are faced with several questions as their trades move into
retracement levels.
1. Take profit?
2. Fight the volatility? (If he or she has considerable reason to believe more bounce
is to come.)
In figure 4.2 and as bounce traders likely expected, the AUD/NZD did hit the 38.2%
Retracement within 12 hours of the low. However, the AUD/NZD sold off again
(twice actually), before making a run at the 50% Retracement. (Again, though we won't
cover the subjects until further on in the book, sustained rebounding, or prior trending
continuation is where volatility/probability will really help traders.)
The bottom line in the AUD/NZD example is jittery traders were likely shaken out
when excess volatility surfaced around the key Fibonacci Retracements.
It's important to mention that those with steadfast stops -just below the low of the
original move, would have not lost their positions. The question is though, can you
risk the loss, or for that matter, giving up profit considering you could have exited at
the 38.2% level?
Here's one way to solve the problem(s). When trading a reversal set your stop as
soon as you make the trade (if you have a non-US account able to enter stops and
limits)… Then, set a sell order for one quarter of your position at the 38.2% Fibonacci
Retracement, so if the trade fails, you will have a small buffer when your stop is hit on
the downside. (You will need to adjust the position size in your stop, if the 38.2%
Retracement is hit; accounting for the 25% of your position, you just sold for a profit.)
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Figure 4.2 (Shown again)
At the same time you made the initial trade, set a sell order for 50% of the total
initial position at the 50% Retracement. In the case of AUD/NZD, when the pair first
hit the 50% Retracement, you would have taken even more off the table…and would
need to adjust your stop order accordingly, as you will now only have 25% of the
original position. Then, with the remaining 25%, you can set another limit order to sell
at the 61.8% Retracement, or let it ride. FYI, from my experience trading Forex, the
61.8% Retracement level seems to hold the most weight… If a pair does not reverse the
bounce at the 31.8% and 50% levels, and you see a 4-hour bar close near the 61.8%
Retracements, there's a good chance the pair will retrace the whole move.
Regardless, the Retracements serve as profit targets for reversal trades, or re-entries
for those who believe larger trending will persist.
You must decide for yourself whether you will trade for larger moves, or quickly
scalp profits on smaller, sudden volatility pops. It is my experience that traders who
take small profit after small profit and cannot hold for larger wins, eventually get killed
when they take a bigger loss. Truly great traders know one of the keys to success is:
…little loss, little loss, little loss, big win…
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…not vice versa.
Thus, attempting to trade bounces is generally a losing proposition overall. Really,
we should attempt to trade with the trend, using Fibonacci Retracements as a tool to
help time our entries.
For traders who think the pair will continue the original move, you can place your
short orders near key Fibonacci Retracement points, where you hope to reenter in the
direction of the big-move trend.
One way to do so is to place an order for 25% of your total predetermined size at the
38.2% mark, 50% at the 50% mark and 25% at the 61.8% mark… This way, you've
allowed yourself 'wiggle room' if the 38.2% and 50% Retracements do not hold. It's
important to note though, that if the 61.8% Retracement is breached –significantly, the
pair will likely retrace the entire move, an event that happens quite often in Forex
trading, especially on short-term charts.
The best rule of thumb in this case is as simple as the old market saying: When in
doubt, get out.
In addition, as we're about to cover, it is a good idea in today's market to actually
place orders above Fibonacci Retracements for short positions and below for long
positions. By doing so, we attempt to starve off volatility from the HIIV Effect
mentioned in Chapter Two. I'll explain this in greater detail in the following pages.
Fibonacci Retracement
Volatility
As we discussed in Chapter Two, indicators are indeed failing retail traders in the
current market.
Fibonacci Retracements are no less affected… The problem is there are simply too
many traders using the same signals, all acting at the same time. Think about it for a
moment… If the entire retail community is watching the 38.2% Retracement as a short
entry point in a downward move, what's the likely result? The result is many, many
traders will also likely act on that same information at the same time, taking short
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positions in the same places at (or near) the Retracement I've just mentioned. But what
happens if a large institutional order pushes the stock, or currency pair slightly above
the Retracement? The result would likely be a massive wave of electronic stop orders
tripping globally, as retail traders stop out on excessive volatility.
The problem is that as momentum begets momentum, stops also beget stops,
meaning once a wave of stops are hit, the actions could cause just enough upside
volatility to trip even more stops slightly higher.
What all of the aforementioned means is that it no longer pays to take a position
'just before' a key technical, or Retracement level.
Too many people are likely doing exactly what I have just mentioned (shorting
before the key Retracement) and as soon as a slight amount of volatility occurs, those
same traders will be stopped out, thus causing an additional wave of volatility. Then,
just a few moments after the entire retail crowd is wiped out, the currency pair will
reverse and travel in the initial direction…leaving 'at home' traders scratching their
heads attempting to figure out how it is they always seem to get stopped out precisely
at highs, or lows… Just before the pair moves in the direction they had originally
anticipated.
To combat this issue, traders should take positions a little 'out of the money' from
key technical levels. What I mean is if you are going to time a short entry with the
Fibonacci 38.2% Retracement, it might be a better idea to wait until upside volatility
hits 40 or 42%, thus using the 'HIIV Effect' (Chapter Two) to your advantage. For the
50% Retracement, we may want to use 55 to 58% and for the 61.8% Retracement,
perhaps 66 to 68%. The bottom line is because of the HIIV Effect, we simply need to
build in a little 'volatility premium' into our perceived entries and exits.
The following chart shows just what I mean… If you were attempting to take a
position short in the EUR/USD using the 50% Retracement as your entry, it would
have paid to wait until the pair was slightly above the Retracement, before taking the
position. The EUR/USD 'popped' just above the 50% Retracement, before falling
through the floor. Those who took positions before (just under) the 50% Retracement
were likely stopped out on the quick pop above and were likely shaking their heads at
'excessive volatility'.
However, the volatility savvy trader simply used the event to achieve better fill
short.
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Figure 4.3
As Simple as a Pitchfork
What I'm about to show you is an incredibly simple technical analysis tool;
however, it is one that not many traders know about, despite the apparent
effectiveness. By implementing pitchforks, traders can quickly identify short and longterm trends, in an effort to find incredible trades, both with and against the trend.
Simply put, using this simple tool, "the trend" could become your best friend, as you
will know when to trade with, and/or against the larger trading paradigm at work.
Pitchforks will also help show traders how to analyze the larger trend, by
identifying the 'median line' of the relevant trend in any given range. Many novice
traders fail to recognize larger trends within Forex, which can often lead to
unanticipated volatility.
With this in mind, we'll start with a explanation of pitchforks, and then use a 'macro
to micro' approach to find our trades.
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As you will see, knowing the larger trend, before we look into shorter-term trades
can not only help us find more optimum entries, but can also help us keep cool when
volatility turns on.
By definition an "Andrew's Pitchfork" is a series of three points in a trend that dissect a
sharp ascending move, or downward trough.
Figure 4.4
The line moving through the middle
the trend forms the middle prong of the
pitchfork, and is known as the 'median
Then, upper and lower parallel lines are
drawn to project ascending/descending
support and resistance and targets within
perceived trend.
of
line.'
the
However, for the purposes of Forex, I
have found through trial and error, that
textbook definition does not work well.
Thus, with one slight tweak, pitchforks
become immensely more reliable for long
short term trading.
the
and
Figure 4.5
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The below 4-hour chart of the GBP/JPY chart demonstrates why connecting three
points does not always work well…
As you can see, by simply connecting three 'lows' in the range leading up to the
trough, we would have an incorrect pitchfork, as the lower line would not accurately
represent the ascending channel.
The reason for the breakdown is simply because we must have equal distance
between the median line and the upper and lower pitchforks, the inaccuracy of the
median line itself promotes a breakdown in the lower ascending support line.
We must understand that there is a bit of an 'art' to drawing pitchforks and at times,
we will need to 'cut' the lows of an ascending trend or the highs of a descending trend,
to create an accurate median line.
To draw pitchforks correctly, instead of trying to draw a trend line from three
consecutive points to dissect the trough, we will simply find only one point to start our
middle trendline with. The point we will use can be the lowest point (or highest, in
the reverse case where there is a sharp rally, instead of a trough) prior to the opening
of the trough. (It's much simpler than it sounds.) Or, we can use the low of the move
(which I prefer) and then cut into the some of the lows, or highs of the move, thus
forming a more accurate representation of the true trend median.
Figure 4.6 shows what I mean… As you can see in the case of the GBP/JPY, I used
the low of the range as my starting point for the median line; however, I did not
connect the lows of the range… Instead, I 'cut' slightly into the lows and dissected the
trough at the precise mid-point. By doing so, I have drawn a more accurate pitchfork,
as noted in the currency pair running up the lower pitchfork, without a significant gap
in-between.
The instance of slightly cutting highs and lows is truly the 'art' portion of identifying
median lines (and pitchforks) something that you will need to learn by trial and error.
However, once you have mastered the ability to correctly identify the (at times)
'mysterious median', you will find much greater success in using this simple, yet
effective, tool.
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Figure 4.6
When we are able to correctly identify pitchforks, we will suddenly find ourselves
empowered with two possible trading strategies:
1. In ascending trends, buy pullbacks on either the lower, or the middle prong, if a
distinctly identifiable trend is in place. By buying pullbacks into the middle, or
lower prong in an ascending move, we are really taking on the age-old market
advice of 'the trend is your friend.' In descending trends, sell the rallies up into the
middle or upper prongs, and you will be short with the trend.
We want to put our stops on the opposite side of whichever pitchfork we have
taken a position on, while also remembering that at times, there will be a slight bit
of volatility breach as well. Like technical indicators are failing and like Fibonacci
Retracements are seeing a slight bit of 'excessive volatility' opposite major
Retracement levels, as pitchforks become more and more 'mainstream', we will
begin to see the same volatility effect taking place. With such in mind, we may
want to take our positions just slightly on the underside of a pitchfork in an
ascending move, and vice versa on a descending move, just to build a little
'volatility premium' into our trade.
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2. If in an ascending trend, the currency pair breaks the lower pitchfork –more than
what we would normally assume is not just a 'volatility pop', turn the trade and go
short...
Quite often, savvy traders will be piling in as well, and you can ride the wave! If in a
descending trend, the pair breaks through the upper pitchfork, a reversal may be occurring
and Forex traders can go long.
To isolate entry and exit points for daytraders, draw pitchforks on 4-hour, 1-hour,
15-minute and 5-minute charts to isolate exact points for scalp trades.
The idea behind walking down through the chart timeframes (even if you're a
scalper) is simply to have a greater idea of the larger 'terrain' at hand.
There's an old cliché that goes something like, 'It's tough to see the forest when you're
in the trees.'
When we only look at 1, 5 and 15-minute charts we have chosen to remain in the
trees. However, even if we're doing nothing but scalping, by at least paying attention to
the 4-hour chart, we have a better idea what the larger forest looks like (from afar),
something that may help us keep our bearings straight when we're in the thick of a
trade.
Really, we're talking about a macro-to-micro approach…
Macro to Micro Pitchforks
Now that we've covered how pitchforks work and the right way to draw technical
tool, let's take a macro to micro approach to finding trades. As you can see in the
following monthly chart of the USD/JPY, the dollar appears to have been losing steam
since 2001. While the greenback was not experiencing an all out descent, the chart
shows the range as more of a 'slowly lowering' occurrence of consolidation. Looking
for some sense of support for the larger multi-year range, we see such in the 100.11
area, just above the massive 100 whole number.
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Moreover, when we look at the larger trend, we see the descending middle
pitchfork is very close to long-term horizontal support on the far right side of the chart.
Amazing! From this chart we know the long-term trend is down and there could still
be more to come… We also know the pair is headed towards 10-year support for the
third time.
Figure 4.7
Next (and please forgive me, as I'm sure Figure 4.8 may seem slightly confusing at
first glance) we have the weekly chart. I have actually drawn three pitchforks on this
chart, one longer-term ascending trend pitchfork, one medium term descending trend
pitchfork and one short-term 'steep' downward trend pitchfork.
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Figure 4.8
Why so many pitchforks you ask?
The point of drawing multiple pitchforks in the first place…is to uncover ALL
possibilities, not just the 'one' that appeases what we want to see.
By the way, I really believe the reason why many traders never win is because even
when they are given the tools to trade, they make the tools, or technical signals 'fit their
preconceived opinion' of the direction they've already decided (sometimes
subconsciously and for no reason really) the currency, or stock should move.
Thus, to uncover some sense of truth, we have to examine all options, not just the
one, or two that seem to fit the opinion we've already decided fits…
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Daily Chart in Action
As the below chart shows, the USD/JPY tagged the lower pitchfork of the mediumterm trend, while also hitting the middle pitchfork of the short-term trend, it's likely a
bounce (if even short-term) could ensue. We also know the currency pair possibly put
in the bottom pitchfork for a new slow-ascending trend as well…
What we have to remember here is that until the upper pitchfork of the steep
descending short-term trend and the middle pitchfork of the medium-term trend are
breached, the trend is still down.
Again, we see confirmation of the downward relevant trend in the daily chart. As
you will notice, should the pair continue to bounce; the USD/JPY will encounter
resistance in the (roughly) 111.50 to 113.00 area.
Figure 4.9
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See, the whole point of pitchforks is simply to visually identify major trend reversal
points and/or trend re-entry points, ahead of the game…
In the present case of the USD/JPY, if the pair is to move above 113.00, we could
assume the recent low (which created the lower pitchfork of the longer-term ascending
trend) is real, and a larger reversal is indeed, in effect.
However, until descending resistance of the short and medium term trends are
breached, risk prevails for the trader attempting to take a long position. This isn't to
say savvy traders can't pick off long moves, however, we have to remember the main
trend is still down. This is knowing the 'macro' trend, or reversal points to help in our
intraday trading.
As we continue to examine the USD/JPY daily chart, we see the pair recently rode
down the topside of the upper prong… Again, it is important to keep in mind that the
pair is trading just above the middle pitchfork of the short-term trend on the daily
chart, with the medium-term trend still showing downside to come.
4-Hour Chart
The 4-hour chart begins to shed more light on the current ascending bounce, giving
us some idea of what to expect in the near-term. As you can see, I've drawn a
'assumptive pitchfork', thinking ascending support of the recent uptrend could actually
be the median line for a possible uptrend to come, should the bounce continue. I've
also drawn in two levels of support, one at relative support of the recent trough and
one at highs of the 'relative range', while the pair was making new lows. What I'm
doing here is attempting to find high probability entry points, should the bounce
continue.
What's also important to note, is that I am also marking a final 'give-point' denoted
as Support 2 (sometimes known as a critical 'pivot point') where bulls will likely toss in
the towel and another re-test of lows is in the cards.
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Figure 4.10
Traders may have wanted to wait for a slight bit more 'guidance' to see if the
present ascending trend would hold… What you can't see here is how volatility and
probability could help determine if more ascending action is to come, or of lateral
trading will ensue.
We will cover volatility and probability in Part Two of Volatility Illuminated.
In the next 4-hour chart (Figure 4.11), we can see the USD/JPY held the lower
'socket' of the perceived Andrew's Pitchfork, which it rode all the way into the 111.50
area, before signaling more downside to come…
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Figure 4.11
The failure in the 111.50 area was then marked with lateral trading action, which
would have prompted us to move the handle of our pitchfork inside the ascending
relevant trend to more accurately reflect the true range 'median line.' Then, after the
USD/JPY made a significant breach of the lower pitchfork after testing the 114 area, we
would have watched support in the 112.50 to 113.00 area of a larger breach of trend…
For courageous swing traders, the final stop should have been the highest high of
the relevant pitchfork trend. However, for newer traders (who should not be taking on
significant risk), zeroing in on a trade, if the pair breaks the prong the trader bought or
sold from…on whatever timeframe chart prompted the entry…close the trade.
Chances are there's a reversal looming, or volatility is about to shake out a ton of
traders.
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Figure 4.12
Regardless, you don't want to be one of the poor-souls who hangs on, only to be
forced to exit at the last moment…taking a whopper of a loss.
Remember: Missed money is always better than lost
money!
Overall, the monthly chart showed us the long-term trend was down… and chances
are the dollar could take another dive. However, the weekly and daily charts were
alluding to a possible short-term pop looming, which confirmed on the 4-hour chart. If
some of the information above seems a little jumbled…it is. See, pitchforks are
continually changing dynamic tools where we must constantly look for changing
ranges and medians… What I have just mentioned is much of the reason volatility and
probability help illuminate some of the choppy action that surfaces in trading daily.
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We will now apply Fibonacci to pitchforks, to create a more useful tool… However,
all 'standard technicals' eventually break down and thus, without the application of
volatility/probability; even Fibonacci Pitchforks tend to mislead traders from time to
time. Again, please note that we will cover volatility and probability in Part Two of the
book.
Note
When trading longer-term reversals, it is always best to wait for significant
confirmation of a trend change, before jumping the gun. Those who try to
trade 'the big picture' without confirmation can fall victim to
presumptuous/impulse-trading and consequently, can incur large losses.
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CHAPTER FIVE
VOLATILITY ADJUSTED Forex
Fibonacci Pitchfork Strategy
Over the following pages, we will see how Fibonacci Retracements and Pitchforks
come together, helping locate high-probability trending re-entries and/or larger
reversals. What is truly amazing about overlaying pitchforks on Fibonacci
Retracements is the simple fact that by doing so, we are attempting to 'trade with the
trend', while also identifying entries that give us clear stop-loss points to maximize risk
management within our trading.
The main principal behind the Fibonacci Pitchfork Strategy is to overlay at least two
pitchforks on top of Fibonacci Retracements, and then look for larger trend entries near
the 50% and 61.8% Retracements.
By doing so we:
1. Maximize major trend re-entry probability.
2. Identify if and when the larger trend is breaking down and thus, close our losing
trade and turn the position in the new direction, attempting to capitalize on the larger
potential reversal at hand.
Here's how it works. In the below daily chart of the EUR/USD, you will see a
Fibonacci Retracements overlaid on the most recent rally, in an effort to find reentry
points for the long-term upward move. We know the relevant trend is up; however,
given strength of the U.S. Dollar through the financial crisis, we cannot completely rule
out more upside to come… Regardless, given the oversaturation of money supply
from October 2008 through the spring of 2009, there could be more strength to come in
the EUR/USD while markets attempt to decipher credit quality of U.S. Treasuries and
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overall 'holding power' of the greenback. With the aforementioned in mind (and please
note that I am always considering the larger 'fundamental picture' even though we're
looking at technicals) there could be a major point of trend continuation (upside reentry) looming.
Here's the thing though, we don't have to have an opinion, we can trade the
upward, or downward moves profitably using the Fibonacci Pitchfork Strategy with
predetermined stops, we just need to be patient about our entries. What I'm saying is
that instead of having an opinion and just 'jumping in' we can wait for high-probability
entry points. The whole point of patiently waiting for these points to surface, is we are
taking positions at major points that even if we are wrong, we can keep stops super
tight, to quickly close the position and then turn it in the correct direction…
The below chart (Figure 5.1) is going to look a little confusing at first, but stick with
me for a moment, and you will see the strategy is actually quite simple.
The foremost trend we have identified is the present ascending pitchfork, with the
handle starting in the 1.2525 area… We know this is the relevant trend, as the recent
high strikes the middle pitchfork almost exactly.
What's more, we have drawn a second descending pitchfork (short-term) from the
high, dissecting what appears to be a small rally from approximately 1.3805 to 1.4170.
We have also drawn a Fibonacci Retracement from 1.2889 to 1.4334. We are now
attempting to identify trend re-entry points for the longer-term ascending move, while
also looking for low-risk short entry points, should recent selling continue… Also,
please note that I have drawn to Schiff Parallel Lines…
While I have modified the definition slightly (to what I find works within Forex)
Schiff Parallel Lines are trendlines drawn parallel to middle, upper and lower
pitchforks, which are equal distance from the pitchfork as the previous 'blip' recorded.
In theory, the stall into a pitchfork or extension slightly beyond, foreshadows a second
stall of volatility, or slight pop beyond the pitchfork line in question.
Andrew's pitchforks used to hold ground (on their own), however, as many
indicators today, we are now seeing 'pops' of volatility beyond what used to hold, per
the traditional definition of the indicator. Simply put, too many people are using the
same tool, which is now causing additional volatility. To account for the slight bit of
'extra volatility' in pitchforks, Schiff Parallel Lines seem to do the trick; at least for the
time being…
Moving on, also in the below chart, you will notice that I have marked two possible
long entry points, one where the short-term trend strikes the 38.2% Fibonacci
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Retracement, and a second where the short-term pitchfork strikes ascending support of
the relative range, while also tagging the 68.1% Retracement…
Again if you remember my earlier discussion of 'excess volatility' in Fibonacci
Retracements and in most technical indicators, should the EUR/USD truly drop into
the 68.1% Retracement, it could extend slightly below the Retracement, while also
slightly violating ascending support on the downside, before starting a new rally…
In today's environment, we have to remember that all technical analysis has a bit of
'art' to it in that excess volatility is creating 'blips' of trading action beyond what used to
seem like clear areas of entry and exit. For this reason, volatility and probability, which
you will read about in Part Two are major assets in helping to find some clarity, when
traditional technical indicators fail.
Figure 5.1
For the time being; however, you can see what I am trying to do in Figure 5.1 is line
up trend re-entry signals with the longer-term pitchfork and Fibonacci Retracements.
What's more, should the lower pitchfork-line (ascending support) fail, I am also
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attempting to see where the pair could still begin to rally, as denoted in drawing the
simple (dashed) ascending support line of the relative trend.
It's also important to note that if the second Schiff Line (slightly downside and
outside of the larger ascending pitchfork) were to fail, momentum short-traders could
take positions, looking for a move into ascending support, where they would then
want to reconsider their positions, potentially looking for an upside move to surface.
I would like to take a moment to drop in a few words of wisdom... Many new
traders never win big, because they don't understand that losses will occur…
However, losses are the one thing (and I mean it…the only thing) you can assuredly
count on 100% in trading. Losses will happen, however, keeping losses small, and
handling situations where our trades are not working is really one of the most
constructive steps to becoming a profitable trader. When loses surface, we must
remember to keep our emotions in check, while sticking to the original trading plan,
knowing our small losses will eventually be offset with large wins.
Moreover, new traders often do not understand that when technical levels are
breached, with relative significance, the trade must be closed. Unfortunately, many
newer traders can sometimes allow their emotions to override the reality at hand...
Here's another trading cliché that I firmly believe in:
The first loss is always…the best loss…
In the above example, the potential damage from holding a long, if major ascending
support were to be breached, is simply just too risky. We must remember that every
single time we take a position; we have to question 'what if?' What I mean by
'questioning' is for every trade we take, we must have a 'turn it' plan in place.
The 'turn it' plan is precisely where we say, "Okay, I mapped out what I thought
was the correct technical picture, but clearly the market is saying something different; I
will turn the trade the other direction now, without an emotional hold on my previous
opinion."
Should ascending support fail, savvy traders would view the small loss as an
opportunity to turn the trade short, knowing that they were moving 'with the market'
and not attempting to force something that just isn't working.
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Experienced traders know that we are never going to be right all of the time, and it
is truly 'how we handle positions that are not working', which separates those who are
profitable, from those who eventually blow up.
With all of the aforementioned in mind, if we now take a moment to drill down into
the 4-hour chart, we begin to see a little more 'guidance' into the possibilities at hand.
The 4-hour chart shows us that we are currently 'mid-range' within the recent selloff
and longer-term support. Moreover, we can also see where a potential long-entry at
the 39.2% Fib Retracement sits at the exterior Schiff Line, drawn just outside of the
larger ascending pitchfork. I have not noted the 50% Retracement as a potential longentry point, as other than lateral support from the relative range, ascending support
(noted on the daily chart) is sitting just below at the 61.8% Retracement… The common
sense 'sniff test' tells us that should the pair continue downward in the near term, the
61.8% Retracement (where ascending support sits), would likely be a more realistic
target, over the 50% Retracement.
Figure 5.2
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Now, stepping down into the hourly chart, we see just how 'mid-range' the
EUR/USD is…
Again, the whole point of drawing pitchforks and Fibonacci Retracements from
macro picture down…is to identify high probability entry points, within the larger
picture. Some traders might be asking, "What about right now, which direction will the
EUR/USD travel?"
The answer is, "I don't know." Well, let me rephrase that… I have a good idea,
based on many technical indicators and the present fundamental outlook… However,
for the example at hand, we want to think:
"I don't know."
Why?
Foremost, even though I personally have a bias towards which direction I believe
the pair should travel, we are still mid-range, consolidating after the recent move up.
What's more, why would I want to guess here, when I could simply wait for a higher
probability entry? Thus, looking at the hourly chart, I have a better idea where the
'higher probability' entries are within the current trading action…and also the longerterm Fibonacci Pitchfork strategy.
As Figure 5.2 shows:
1. I can attempt to take a long position on the lower Schiff Line, just below the lower
pitchfork of the ascending trend. At this level, if were are not dropping rapidly, or
any EUR/USD bearish news has surfaced, I would likely attempt a long, placing
my final stop just below the 38.2% Retracement, which we will call the support zone.
2. If the EUR/USD breached the support zone, I would likely then turn the trade
short, expecting an extended volatility selloff and a move potentially down into the
61.8% Retracement.
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3. If the pair held the 38.2% Retracement (knowing the key Retracement would likely
be breached slightly because of the HIIV Effect in today's market), if no news
surfaced changing my larger bias from long to short, I may attempt another long
trade, looking for the ascending trend to stay intact. I would place my long stop
just below my entry, likely in the 44% Retracement area (not pictured), which
(with a little common sense) you can calculate by hand.
4. Should the pair fall all the way into the 61.8% Retracement, I might attempt to pick
up another long position; however, I would search high and low for some sort of
news providing transparency as to why the 38.2% Retracement and ascending
support of the lower pitchfork did not hold. Fundamental news is always king
and trading without looking for changes in fundamental bias, and/or assuming
technicals will always 'tell the truth' is simply reckless.
5. Backing up to my original long entry (denoted as #1 in this string), if the
EUR/USD never actually fell into ascending support and instead breached upper
pitchfork descending resistance of the shorter-term relevant range (likely
witnessed by a move above 1.4080), I may take a small 'breakout' long position too.
However, there would likely be news prompting the trade… For a trend to
continue (breaking out of consolidation) there is usually some sort of fundamental
news to accompany the trading action.
Again, a little common sense goes a long way when overlapping what we see in
technicals to the news unfolding within markets.
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Figure 5.3
Overall, as you can see, by overlaying pitchforks and Fibonacci Retracements, we
have created a strategy that:
1. Helps us identify the 'larger trend' and critical levels within the relevant
range.
2. Identified Fibonacci Retracements for the larger move at hand.
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3. Located trade entry and stop loss points for 'with the trend' trading, while
also enabling us to take quick positions against, should the situation
warrant such.
4. Located larger 'reversal points' where we know to look for a shift in
fundamental mindset.
5. Created a clear plan for trading with the trend, but also helping to
understand when and where we should consider turning the trade, should
a reversal occur.
6. Produce a slight sense of peace, knowing that we are trading with highprobability entry and stop loss points…
Again, I would like to mention that even with all of the technical mapping in the
world, excess volatility in today's market will cause pitchforks, Fibonacci Retracements
and even Quad CCI (which you're about to read in Chapter Six) to breakdown. Thus,
in Part Two, we will dive into volatility and probability, providing even more insight
into today's market.
Towards the end of the book, we will then overlap Fibonacci Pitchforks and Quad
CCI with volatility and probability and as you will see, we will unearth an amazing
sense of clarity most traders never find.
In the mean time, I would like to reiterate a few trading rules that we must always
remember…
Rules to follow
1. All of the magical math in the world will never make Fibonacci Retracements
true 100% of the time. Period.
2. A little common sense goes a long way when using any type of mathematical or
technical indicator to trade from.
3. If the market is showing something different than what the indicator is
presenting in the current market, the indicator is wrong.
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Signals from indicators do fail.
4. Fibonacci Retracements are only good so long as enough people are watching
and acting on the same information (the collective whole) to make the signal
true, however, too many people acting on the same information at the same
time…causes excess volatility.
5. Again, even if you've opened a trade based on Fibonacci Retracement
expectations, be prepared to close the position, should common sense warrant
such.
A Few Final Notes
The trading example in Chapter Five utilized live charts… I did this for two
reasons:
1. Anyone can find a trade that works historically; however, real traders
know…what looks good historically…hardly ever works in real time… Thus,
the example above with the EUR/USD is/was created in real time…
I do not even know what the outcome will be, as by the time history cements
itself, this book will be on the printing press…
2. To show readers that even though Fibonacci Pitchforks lack volatility and
probability edge, they do still work…that is, with a little common sense…
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CHAPTER SIX
QUAD CCI – THE TRADITIONAL
VOLATILITY PARADIGM
Within Forex, there's a term professional traders often throw around when
referencing the retail community… Retail traders are frequently cited as doing nothing
more than just 'chasing indicators'. Sadly, so many retail traders fall victim to the
mindset of believing trading is easy and/or if they just uncover the 'secret technical
code', they will never lose again. With this mindset, it's no wonder these same traders
unfortunately constantly find themselves on the wrong side of the eight ball when
volatility kicks in.
However, there is another way to trade…
Throughout Chapter Six, traders will gain more insight into how and why 'chasing
indicators' is such a losing game, while also seeing how traders can begin putting
indicators back on their side…to overcome destructive volatility that overwhelms most
of the retail community daily.
However, it is important to remember that while the Quad CCI strategy you're
about to read about is something I personally use, I overlap the strategy with volatility
and probability, WVAV and WAVE • Price Mass to gain greater insight into whether
the signals produced are real, or are really just 'those old charts fibbing', yet again.
While the discussion on multiple CCI time periods is certainly not a "one stop shop"
to completely navigate the larger universe of trading stocks, futures, commodities and
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Forex, using the indicator correctly can definitely assist traders when markets are
offering little guidance.
Take a look at the below hourly chart of the EUR/USD, which shows the basic 'feel'
of the Commodity Channel Index (CCI), at least, as most traders use the indicator.
For the most part, the indicator is used to look for reversal (or trend re-entry points)
when the indicators falls from above +100 back under +100, or up from underneath 100, above -100.
What you will hopefully notice right away is the first 'sell' signal (from the left) and
the third buy (also from the left, which I've marked with an asterisk '*'), both provided
false signals.
Figure 6.1
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To understand why the false signals could be appearing, we need to take a closer
look at the indicator overall… According to one major Website, (I'm keeping their
name anonymous to not drag them through the dirt, though I have notified them of the
error):
"An oscillator used in technical analysis to help determine when an investment vehicle has
been overbought and oversold. The Commodity Channel Index, first developed by Donald
Lambert, quantifies the relationship between the asset's price, a moving average (MA) of the
asset's price, and normal deviations (D) from that average. It is computed with the following
formula…"
Here's where we begin to split hairs on a few important matters that I believe you
should be aware of…
The Website is correct that CCI was developed by Lambert (in 1980, FYI), moreover,
the definition is also correct in that the indicator is meant to help determine overbought
and oversold areas… However, CCI was also developed to help find 'cyclical swings'
of commodities and other financial instruments. What's more, in the above definition,
you will notice the use of the terminology 'normal deviation.'
Just to make sure I'm not completely losing my mind, I checked about twenty
different Websites for definitions of CCI while writing this and what I've found is that
almost all mislead readers using the same, or similar terminology…setting you up for
failure.
The problem is likely because most of the information on trading-related
Websites is written by people who don't really trade in real life…they don't even
know the crap they are regurgitating is wrong.
I like to think of the situation similar to a rocket scientist explaining how to smooth
drywall mud almost perfectly…in one shot. Though the task might seem easy overall,
unless you've actually done it a few times, there's no way you'd know the tricks of the
trade, or the 'inner workings' of how drywall mud sets on the wall and in the bucket, or
even how important the 'art' of trowelling is. (I learned the hard way renovating a
house many years ago… For the rest of my life, I will have an immense amount of
respect for drywallers. And let me tell you, I mean it too!)
Back on subject, in most definitions of CCI, we often hear terms like normal
deviation, or standard deviation as part of the equation. However, what we must
understand…is that CCI is calculated using mean deviation (or mean absolute
deviation MAD), not standard deviation.
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Moreover, there is no such thing as 'normal deviation.' (Just to split hairs, Roget's
21st Century Thesaurus, Third Edition lists 'normal deviation' as a synonym for
standard deviation; however, standard deviation is not used calculating CCI, mean
deviation is.)
Furthermore, what the heck is 'overbought' and 'oversold'? As you're about to see,
when CCI is trading above +100 and below -100, whatever financial instrument the
indicator is measuring may not be overbought, or oversold at all…
I'm not kidding, the stuff most Websites feed traders is just plain damaging…
To dig into the specifics, CCI is calculated using the 'mean deviation', which is
thought of as providing greater accuracy to non-normal (non-Gaussian) data than the
more commonly used standard deviation.
In the paper Revisiting a 90-year-old debate: the advantages of the mean deviation by
Stephen Gorard (presented at the British Educational Research Association Annual
Conference, University of Manchester in 2004), the author asserts, "In those rare
situations in which we obtain full response from a random sample with no measurement error
and wish to estimate, using the dispersion in our sample, the dispersion in a perfect Gaussian
population, then the standard deviation has been shown to be a more stable indicator of its
equivalent in the population than the mean deviation has. Note that we can only calculate this
via simulation, since in real-life research we would not know the actual population figure, else
we would not be trying to estimate it via a sample."28
I understand why mean deviation is used in CCI (to attempt to compensate for nonsynthetic, non-perfect Gaussian price data); however, after spending much of the past
year mapping distributions in markets, I would argue the shorter the timeframe
measured, the more 'bell shaped' data becomes.
What I'm saying is perhaps the formula for CCI is more accurate with a greater set
of data and that perhaps on shorter timeframes, the formula needs to be changed to
utilize standard deviation, over mean deviation. Don't worry though, we will change
the formula on your charts, without actually changing the formula at all! I'll explain in
just a moment…
Below is the formula for CCI, please don't worry about digging too deep into the
math… You don't have to crunch the numbers, I would just like for you to understand
'the philosophy' of what's happening, over the mathematical fun-o-rama calculator
super-time. The philosophy is what matters…
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CCI is calculated as:
CCI = (TPn - TPSMAn) / (MD * 0.015)
Where
TPn = Typical Price (High + Low + Close)/3
TPMA = SMAn = [(TP1 + TP2 + TP3…+TPn)/n]
Then…
CCI =
[[TP current period – TPMA current period]
Divided by
[((TP1 – TPMA1) + (TP2 – TPMA2) +…TPn + TPMAn))/n]]
All multiplied by 0.015
Okay, so where the heck is all of this going? The whole point of CCI is really to
measure the major 'Containment Zone' of a commodity, stock, currency, or whatever…
However, like everything else in the market that's totally misleading and confusing, for
whatever reason, the whole point of CCI (as explained by 90% of the Websites out
there) is as well.
Definitions of CCI state 'cyclical swings', major price movements and reversals,
deviation this and that…yada, yada, yada…
Here's what's really happening…
Imagine a teeter-totter that has values from -500 to +500, with zero being the middle.
I place a bowling ball on the teeter-totter and get it rolling to the right side towards
+500 and then tell you that you can't let the ball roll off the end, but the rules are you
can only touch the teeter-totter and not the ball itself, what would you do?
Most likely, you would move to our left and push down on the opposite side of the
teeter-totter (the -500 side) to get the back rolling back towards the middle.
Now, imagine that I had drawn -100 and +100 on either side of 0 (zero), which right
now, because you are pushing down on -500, the ball is rolling back towards.
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It would make sense that when the ball is rolling back from the +500 area and
crosses over +100 towards the 0 (zero), the ball would likely cross zero right?
Right?
Right…
However, please also imagine that I've drawn the numbers slightly awkward to
common sense in that the further from zero we get (conversely, the closer to -500 and
+500 the ball is), the more densely I've drawn the numbers grouped together…
As a picture tells a thousand words, I've drawn the teeter-totter for you, as a bit of a
visual aid.
Please see Figure 6.1 on the following page and please excuse my art… The main
point is via Chebyshev's Theorem in statistics, we know that (on average), about 75% all
data will rest within two standard deviations of the mean.
(In the case of a normal Gaussian curve, the probability is actually nearly 95% of all data
should sit within two standard deviations of the mean, thus, in using mean deviation, Lambert
was likely attempting to accommodate for non-perfect bell-shaped data. Moreover, Lambert was
likely also using Chebyshev's Theorem to justify the containment range of -100 and +100,
implying 70% to 80% of all data, which is why he used 0.015 as the multiplier…)
Just FYI Chebyshev's Theorem states:
"The proportion of any set of data lying with K standard deviation of the mean is
always at least 1-1/K2, where K is any positive number greater than 1.
For K=2 and K=3, we get the following results:
 At least 3/4 (or 75%) of all values lie within 2 standard deviations of the mean."
 At least 8/9 (or 89%) of all values lie within 3 standard deviations of the mean."29
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Figure 6.2
Also, please note that in the real CCI, -500 and +500 are NOT the final outlier values
the indicator can move to…
Theoretically, CCI could travel infinitely up, or down… However, on a common
sense basis, people don't have to buy, but they do have to sell sometime, and thus,
prices (and CCI) will never travel infinitely in one direction.
The basic point here is that when CCI crosses back under +100, or back above -100,
the theoretical underpinning is prices are moving back into a more 'normal range' after
just having witnessed a period of extreme activity. What we're looking at is really just
a measurement of 70% to 80% of the expected statistical range for whatever time period
we're gauging …
You might not be jumping up and down in your seat right now, but wait a moment
and I think you could be… Though the above sounds both simple and boring, I like to
think of anything that could make hordes of money…as the exact opposite…
Amazingly, I would bet (without too much trouble) about 99% of all retail Forex
traders don't ever even know what they're looking at when they use CCI to trade
with… No wonder they have such a difficult time making money with the indicator!
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Honestly, by simply reading these pages, you're in the 1% elite who actually know
what they're looking at when they are trading with CCI…
So what we know is this… CCI is NOT indicating overbought or oversold whenever
the indicator moves above +100, or below -100. Instead, CCI attempts to measure
illuminate the 'Containment Zone', which is intended to be 70% to 80% of the total
range. Again, the 'Containment Zone' is denoted as the area in-between -100 and +100
in the oscillator.
What I'm saying is this… In theory, when CCI is trading above +100, the stock,
currency, commodity, or whatever is thought to be trading towards the top of the
larger, typical range, and is in essence trading at, or above +1.2 to +1.5 standard
deviations (using the term 'standard deviations' merely for the sake of example, knowing
standard deviations are not used in the actual calculation of the indicator.)
Conversely, when CCI is trading below -100, we generally assume the financial
instrument measured is trading below the larger, normal range and is experiencing a
period of volatility, denoted most often a sharp or prolonged selloff.
Here's where CCI gets very interesting for those who understand what they're
looking at…
On the below chart (and I apologize for the likely confusion, it was difficult to get
everything in the image even remotely clearly) you will notice what looks like fire, or
hair, or something growing from the left side…
What the mysterious wig-looking thing truly is showing…is an actual
representation of the 'distribution' of the price data on the chart. What we've done is
literally – visually mapped - the distribution of data, so that you can see the
distribution unfolding through trading action…
Here's what readers MUST make clear in their minds:
What we are really looking at when we look at any price data…is data. The data
is forming one HUGE distribution over all time, or a series of subset distributions,
on smaller timeframes.
Notice there is outlying data towards the upper and lower end of the distributions;
however, the bulk of the data rests in the middle; hence the higher mountain-like 'peak
thing' towards the center.
What you are seeing is, in essence, the Central Limit Theorem in action. In
statistics, the Central Limit Theorem says if we pluck a small subset of data out of a
larger skewed range (the totality of market data is skewed, since time is skewwy
skewness in itself), the subset should (for the most part) retain a Gaussian bell curve
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like shape. What you are seeing on the chart is exactly the case in point. For those who
are interested, in the final chapter of Volatility Illuminated, I will discuss subset
distributions further (which are really amazing and complex animals in markets);
reserving the 'mega-in-depth-conversation' for last. (In reference to my own 'best for last'
hype just deployed – and if you remember Chapter One, I have a 50,000 mega-fog-mouth-lamp
too! Just kidding. Anyway, the topic of distributions exposes Poisson distributions as a regular
facet of markets as well, thus, given the extent of the discussion required, I will hold off on the
exchange until the end of the book.)
Now, taking a look at Figure 6.3 (below) we are able to easily identify that (indeed)
trading action is - data - forming distributions. It is vital to 'show' the distributions, so
that readers visually perceive why understanding (at the very least) the conceptual
framework behind descriptive statistics is so important in day-to-day trading.
The bottom line is to be better traders, on the whole, we absolutely must understand
that the action unfolding on our charts is really nothing more than: data.
Figure 6.3
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Moreover, as you're also about to see, CCI is really an attempt a measuring 'mean
reversion' and or 'divergence' of the data. Divergence is fancy-talk for 'trending',
'moving outside of the Containment Zone', or 'geez Zeb, lookie that thang go.'
I personally think the below chart (Figure 6.3) has many, many implications within
trading and volatility; which I hope you will see too.
Please take a moment to notice the lower oscillator, where I have attempted to draw
lines from the actual CCI 'convergence points' at +100 and -100 (meaning the points at
+100 and -100 where CCI breaks from outside the containment area…back within) up
to corresponding squiggly lines in the actual chart itself.
Though my connecting lines (from CCI to the squiggly lines on the chart) are not
straight, a vertical line drawn on each would connect the points. What you will notice
is the CCI convergence points line up almost precisely with the USD/JPY turning back
into the middle range (upwards and downwards) of the channel looking thing that is
overlapping the actual price action on the chart.
What are the channel lines on the actual chart and how is it that they (almost
precisely!) identify the same mean-convergence type of action as CCI?
Believe it or not [insert dramatic pause] I've drawn Bollinger Bands on the USD/JPY
chart as well.
However, what so many traders don't understand is that Bollinger Bands are really
a visual display of potential distribution wingspan, as denoted through the visual
mapping of standard deviations. (I will discuss Bollinger Bands in detail, in the second
half of the book, just FYI.) Sadly though, so many retail traders never even change the
input variables (standard deviations) within Bollinger Bands, while also failing to even
understand what the indicator is presenting in the first place.
Bollinger Bands come preloaded in every charting package (on the face of the
planet) at two standard deviations, which most traders never even think to change…
However, in my humble opinion, to truly unlock the 'power' of standard deviations
as a measurement of volatility and probability within trading, we must change the preloaded default variables. Again, I will discuss standard deviations in great length in
Part Two of Volatility Illuminated.
Anyway, I have changed the values in the below bands to 1.25 standard
deviations…
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By doing so, I'm measuring just over 70% of the total potential 'containment' of the
distribution at hand.
Does what I've just mentioned sound a little like CCI?
It should, because we're basically looking at the same thing; however, CCI is
calculated with mean deviation (or [MAD] for Mean Absolute Deviation), while
Bollinger Bands are calculated using standard deviation.
Overall, yes I had to tweak the standard deviations setting in the Bollinger Bands
slightly, but really, the two are one in the same. (FYI, just in case you might be
wondering, the Bollinger Bands are measuring 14-periods of data, just as CCI in the
chart.)
Here's where the story gets even better… Have you ever had trouble identifying
trend? Or, have you taken a position that suddenly goes against you and you look
back and say, 'ohmygosh that was ridiculous, what was I thinking?!'
If you've ever been in this place of brilliant trading euphoria, what I'm about to
present could help tons.
See, when looking at shorter-term periods, many traders often mistakenly take a
position against the longer-term trend, based on CCI reversing down from the +100oscillator level, or up from below the -100-oscillator level and thus, find themselves in
big trouble when the longer-term trend resumes.
And really, I understand why they're making this mistake…after all, if they had
learned about CCI through just about any trading related Website on the Internet, they
would think above +100 is overbought and below -100 is oversold. Really though,
above +100 means "moving above the first standard deviation", while -100 means "moving
below the first standard deviation", both of which mean, "subset distribution on the move –
alert – alert!"
So how do we defeat this potentially misleading and costly pitfall? We identify
trend.
Note: Please always remember to walk down through all your chart timeframes
(macro to micro) from monthly to weekly to daily to 4-hour to hourly to 30-minute to
15-minute to 10-minute and so forth… Walking down through the charts is the best
way to identify trend from the wide-scope monthly all the way into the minutia of the
minute.
Again, we're simply attempting to keep the forest in our mind's eye, when we're in
the trees.
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Specifically to identify trend though, please look at the below 4-hour chart of the
EUR/USD… I have added in 1.25 14-period standard deviations with 14-period CCI.
What I think you will notice is that when the EUR/USD is traveling near the mean,
we're basically 'trendless.'
What's more, in those peculiar times when CCI is actually trading below -100, it is
precisely when the EUR/USD was staging the largest and fiercest moves downward…
Conversely, just when the EUR/USD traded to the top of the 'Containment Zone',
we failed.
But how many people would have known to associate the move downward below 100 in CCI as 'big selloff to come'?
Figure 6.4
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What's more, how many would have known to spot the 'failure coming' at the top of
the range as well? I can assure you not many…
Here's why…
Because we're taught to use CCI as a tool for reversals, or trend-reentry (still a type
of reversal) we're not taught that the breach of -100 and +100 actually means the stock,
currency, commodity, or whatever is really headed towards, or trading outside of the
first standard deviation, which is exactly when and where the steepest moves occur.
We're taught to look for CCI to cross back into the middle from above +100, or below -100.
I would like to argue; however, some of the best trades are waiting for CCI to slip
outside of +100 and -100 and then trading 'with the trend' or with momentum, or
'volatility'. Then, when CCI comes back across +100 and -100 (after we've participated
in the trending move), we can close our positions and let the 'containment-area
trendless chop-chop traders' slug it out.
On the top of the range, you will also quickly notice that we were already in a
descending trend when the EUR/USD was trying to make new highs… But really, the
EUR/USD wasn't making new highs, it was just trading to the top of the Containment
Zone in an already descending trend, which is also likely, one of the best places to enter
'with the trend' for those who just love those mean reversion 'CCI crossing back
towards zero' types of positions.
I don't know about you though, but there's nothing I hate more than getting stuck in
choppy lateral trading, so often, I look for the breakout, or breakdown from the
Containment Zone, after (and only after) an identifiable trend is in place.
Okay… we should now see that at times, identifying trend (with CCI) can be almost
as easy as simply adding 1.25 standard deviations to our charts and keeping an eye on
BOTH CCI and the Containment Zone.
Why is it called the Containment Zone?
Because I just made it up… Okay, other than that, unless you have some insight into
fundamentals, volatility/probability, order flow, or hopefully another technical
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analysis magic trick, the only thing you get in the Containment Zone is a date with
Mean Joe Green…
Where the 'mean' sits…is where the 'bulk' of our data should sit. The 'Containment
Zone' is statistically (if we're measuring 1-standard deviation on either side of the
mean) where approximately 70% of the data should reside. And in the case of the 1.25
standard deviations, we're really looking at a little over 70%.
What I'm saying is if you're taking a position at, or near the mean, without having a
really good reason for doing so, the position could just as easily reverse against you, as
work in your favor. If you're on the mean, you're on the hill, on the top of the triangle,
at 50/50…tossing your cash into the mystical Forex roulette wheel.
As I just stepped away from my screens for a cup of coffee… I realized that perhaps
I'm being a little harsh on old Mean Joe Green… There are actually times when we can
take a step into Green's house and walk away unscathed… With the aforementioned in
mind, we'll take a few moments to show how we can take positions into the mean,
while also using CCI in a more traditional fashion. However, we're not going to use
the 'same old' one-line in an oscillator trick…
Just to be on the safe-side, we're going to overlay four CCI's to form the 'Quad CCI
Strategy.'
Does this thing sound like a wicked new Bic® Razor, or what?
Standard Stan And The Four
Horsemen
When I first started writing about CCI a few years ago, there were only two…
Somehow, the dynamic duo grew into 'The Four Horsemen'. I guess if I write a sequel to
this book in a few years, there might be two more… Maybe I'll call it: Six Pack CCI.
Yes, I know I'm not funny.
Jumping right in, over the following pages we will learn how to use CCI to identify
trend…to defeat false CCI signals, while also attempting to time positions 'with the
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trend' both inside and outside the Containment Zone. All of which can be efficiently
accomplished by applying two four CCI time periods to the same chart.
Our goals in doing so are to:
1. Prevent ourselves from taking positions against momentum.
2. Time our trades with short-term 'wrist-rocket' thrust from the larger market
momentum.
3. Clearly determine whether the trend is up, down, or sideways.
Foremost please note that I have provided MetaTrader code for 'two CCI' at the end
of the book, while having also made the code available on
www.WallStreetRockStar.com and fxVolatility.com.
After the code is copied into your MetaEditor / MetaTrader Indicator folder, you
should be ready to go. Also, please note that if you do not have MetaTrader, you can
simply stack four CCI indicators windows in one of the various free charting
applications available on the Internet. For those who use the popular charting Website
Stockcharts.com, you will only be able to stack three CCI's one above and below the
chart and one in the actual chart window… I've already prepared a chart for you and
you can access it at:
http://stockcharts.com/h-sc/ui?s=$INDU&p=D&b=5&g=0&id=p53666348969
Moreover the code I am supplying only contains two CCI's in one widow, this is to
prevent excess confusion with too much happening in one oscillator window. To see
all four CCI, please stack two windows, as you will see I have done in the examples
throughout the remainder of the chapter.
If you are using MetaTrader (it's free, by the way… [and] some brokerage demo
accounts [United World Capital, for example] will allow tracking stocks and
commodities too), after you have placed the files in your Indicator folder, please close
and reopen MetaTrader. Assuming the file is in the right folder, the indicator will
show up in your "custom indicator" drop down menu within your charts. Add the
Two CCI code twice, using 14 and 100-periods in the top window and 50 and 200periods in the lower window.
Standard Sam, the Deviation Man will help keep The Four Horsemen in check as the
trading day rolls out…
Mark Whistler
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Page 118 of 308
To see Standard Sam, please add a 50-period Bollinger Band(s) to your chart, set at
1.25 Standard Deviations (STD). Also, as you have likely noticed, I am using a chart of
IBM (NYSE: IBM) to show that the quad CCI strategy (really though, all of the strategies in
this book) work with stocks, futures, and commodities too.
Figure 6.5
As you can see, in the lower two windows, the 100-period and 200-period CCI's are
denoted in the thicker black lines, while the 14-period and the 50-period are shown as
the thinner in each window.
Then, on the actual price portion of the chart, you can see that I have drawn the 50period moving average and two 1.125 standard deviations, which as you likely already
have guessed, should line up with the 50-period CCI as the casing of the 'Containment
Zone'.
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Readers should immediately notice that the two thicker CCI lines (the 200-period
CCI and the 100-period CCI in separate windows) are both traveling above zero.
Plain Jane, the trend is up. Here's what I would like to mention for newer traders…
If you're having trouble deciphering trend direction, drop in quad CCI on an hourly or
4-hour chart …. If the two longer-term CCI's (200 and 100) are above 0, common sense
tells us there's more bullish momentum, than bearish and vice versa for below zero.
While this may sound simple, don't scoff, I know plenty of 'tenured traders' who jump
at every volatility spike, like it's a massive trend change… However, it takes more than
a quick 'spike' to move the 200 and 100-CCI's above, or below the zero line, thus the
resilience of the indicator within itself, can be a great buffer for 'on edge' nerves,
analysis paralysis, and/or muddled vision for whatever reason.
Looking at the below chart…
Figure 6.6
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Traders seeking to take a position 'with the trend' can attempt to purchase pullbacks on
the mean (yes, Mean Joe Green) if:
1. Longer-term CCI (at least the 200 and 100) are above zero…
2. The 50-period CCI is not below -100.
3. Common sense seems inline.
What you will notice is that if we time our long-entry when the 14-period travels back
up from underneath the -100 area, we are using the shorter-term indicator as a sort of
'wrist rocket' to step in just at the right time when momentum is seemingly in our
favor. What's more, by taking a position on the mean (while timing such with a 14period pop back up into the Containment Zone) we have also given ourselves a clear
stop loss point, should the market fall apart. We simply place our stops on the
opposite side of the mean, knowing a breach will likely have the pair testing the lower
end of the Containment Zone…
Please remember: The first loss is always the best loss.
Anyway, should the pair pop up into Standard Stan in the 1.25 area… Once we're
above the standard deviation level, we can actually use the visual identification of the
'Containment Zone' as our stop to ensure we exit the trade profitably…
Thus, savvy traders needed to only wait until the 14-period CCI 'reloaded' and
crossed (the trigger) back above the -100 oscillator containment area reentry point to
implement long positions. What we 're really doing here is using The Four Horsemen
to guide our way…
The 100 and 200 are like big burly swordsmen, which are hard to budge without
significant force. The 50-period CCI is more like the guy who's fast on his feet, but still
tough enough to take on the big dudes… And the 14-period is similar to the scout of
the party…
The fastest of the bunch, but also the first to turn-tail at any sign of danger…
Basically, when we see the 100 and 200-CCI stay above the 0-line, we can infer there
really isn't any reason for them to move out of their range… The 50-period CCI will
sometimes venture over the 0-line, before the hefty battlers, just mentioned…
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However, the 14-period will often venture (quickly) way out into the yonder…and he
will always return to tell his pals what he's found. Crossing back over the 100-line,
traders can take 'rocket trend reentry' positions (usually on the median); however, we
still want to keep an eye on the flighty 14-period CCI character… If he crosses back
over the +100 or -100 level he was just scouting, it means the larger weighted CCI lines
could soon to follow too, as the whole bunch runs from larger momentum on the
way…
Just to mention the opposite situation from what we covered in the two charts
above, if the 100-Period CCI were trading below the 0-baseline (meaning the stock,
currency, or commodity is likely trading right at the 100-period moving average (mean)
as well) and the 14-period CCI spiked above the +100 oscillator level, the trader could
look for a short entry, assuming the 100-period CCI had not begun ascending
(attacking the 0-baseline), at the same time.
I'd like to mention that aggressively taking positions before CCI lines actually
breach the +100/-100 oscillator levels, falling/rising from upper/lower extreme ends of
the indicator window is extremely dangerous.
Moreover, as the 1.25 standard deviation representation on the chart shows,
movement above +100 and below -100 could indicate a larger spike of momentum to
come.
With all of the aforementioned in mind, we will now look at one final aspect of CCI
– Identifying Reversals.
Identifying POTENTIAL Reversals
with CCI
Identifying reversals can be slightly trickier than timing 'with the trend' positions, as
anytime we are trying to take a larger contrarian position against the trend, we are
truly fighting momentum. However, as in life, all things eventually - always - come to
an end, trends eventually…stall…and cease too.
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Thus, to spot potential larger reversals at hand, we will use the +100 and -100
Containment Zone lines (again), applying the 100-period CCI; however, unlike the
above example, we will only use one CCI window, instead of two. What's more, in our
single CCI window, we will also draw a 21-period CCI, leaving the 50-period and 200period CCI's out. I'm making this change for two reasons:
1. At times, we must 'switch up' the lens, which we're observing the market from,
especially if we are not seeing markets clearly.
Figure 6.7
2. Using the 21-period gives us a sort of 'middle
ground' between the jittery trading action of
the 14-period CCI and the more stagnate
movement of the 50-period CCI. Basically, if
your intuition is telling you a reversal might be
on the horizon, but you are not able to see any
real signs of such within news, fundamentals,
or your charts…you can always switch-up
timeframes, or indicators (if even momentarily)
just to turn over a few more stones.
We're actually going to use the longer-term 100period CCI line as inference and confirmation of a
potential downside and/or upside reversal, even
though the line may be trading above (in the case of
a bull trend), or below (in the case of a bear trend)
the +100 or -100 Containment Zone lines…
I'm not really a big fan of using the 100-period
(or even the 50-period) as an indicator of reversal,
through mean convergence from outside the Containment Zone… However, because
what I'm now discussing is the 'usual' way CCI is used, I must mention it. Please keep
in mind, that when we attempt to identify a reversal with the 100-period appearing as
if it is about to cross from above or below the Containment Zone –back into the
Containment Zone, the seconds of data that transpire while the 100-period is actually
crossing back into the Containment Zone can be (what feels like) and eternity of
volatility with the currency, or stock bouncing around, before finally making the move
back into the mean. The bottom line is that if we are going to trade reversals back into
(and through) the Containment Zone we must be prepared for excess volatility as
traders duke out uncertainty.
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Anyway, the main rule is this: The 100-period CCI line must be trading well above
the +100-line level, or below the -100-line, before even thinking about a reversal.
If the 100-period CCI has just barely traded above the +100-containment line, and
then fails, we might assume that simple mean-bound choppy trading is really the name
of the game in the near-term, instead of looking for a larger reversal. (That is, unless
some sort of fundamental news has surfaced making us think differently.) What I'm
saying is if CCI is just "flirting" with the topside +100 oscillator level, but did not make
a pronounced move above, implementing a short position would likely be more
presumptuous than calculated.
To hammer home my point, when the 100-period CCI line is trading 'almost at', or
above the -100-Containment Zone line, taking a short position is a low probability
scenario, as jittery trading could easily bring about a pop up into the mean, or higher,
where we would likely be stopped out.
High probability (overbought) reversals [meaning the bull-trend could be nearing an
end and a sharp downside move could potentially be pending] generally surface when both
short-term (21-period) and long-term (100-period) CCI lines are trading well above the
+100 oscillator level, or below the -100 oscillator level.
When the short and long-term CCI lines are at the extreme ends of the oscillator,
'trend capitulation' or 'the fifth wave,' in terms of Elliot Wave Theory could be in effect.
I would like to mention that several years ago, it seemed like CCI rarely moved
above, or below -250, or +250 in the CCI oscillator; however, with more volatility these
days…the occurrence is commonplace. Thus, when I mention 'extreme values' within
the CCI oscillator window, we must remember to use common sense, while also
making sure to note that increased volatility in the current market, could push values
further above and below +100 and -100 than in recent years.
You may have noticed in Figure 6.7, when the 100-period CCI-line was trading well
above the +100 Containment Zone line (not "just flirting" with it), the occurrence
foreshadowed a large reversal looming on the hourly chart, which could have provided
significant opportunity for savvy traders.
What's more, you will also notice that the 21-Period CCI line crossed BELOW 100period CCI, while STILL above the +100-Containment Zone line…and then
subsequently fell under +100 towards the mean. In essence, we are basically saying "I
want to see longer-term momentum rapped out with short-term momentum also
overheated, before even considering the possibility of looking for a reversal."
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It's important to note traders will need to configure their CCI time periods to best fit
each chart timeframe traded; however, 21-period and 100-period CCI can be used as
initial benchmarks.
Moreover, never ever, ever, ever, ever, ever, ever, ever trade without a stop and
never take on more risk your account can handle. When in doubt stay out.
While there a many more examples of CCI trading, everything we've discussed here
are a great starting point for traders who are not only seeking to help identify trend –in
an effort to increase discipline– but may also help one identify reversals and most
importantly…give additional guidance when to 'stay out' of the game, should choppy
mean-bound trading seem in the cards over the near term.
With everything that we've covered in Part One of Volatility Illuminated, I'm
thrilled to now move into Part Two, where we will really dive into volatility and
probability, while also taking a very close look at VWAP and of course WVAV and
WAVE • PM.
The information you are about to read –as far as I know -is nowhere else readily
available for traders within markets, or on the Internet. I have spent hundreds of hours
preparing the following pages of Volatility Illuminated.
The information you're about to read is NOT a re-hash of someone else's stuff…
What you are about to read came from REAL trading, which I discovered only after
countless hours grinding it out in markets with real money.
Some of the gems you're going to read about were discovered through massive
losses (always a great place to discover incredible insights) and some were unearthed
through long strings of wins, carving out similar data (outside of traditional market
knowledge) to refine and shape in preparation of the information here.
What I'm saying is even if at the end of the book, you're like, 'geez, that sucked, I'd like
my money back,' I'm okay with it, because I plan on using the information here in my
own trading –because it was derived from REAL trading– not sitting behind a 'strategy
tester' looking back into history.
What you're about to read was uncovered with real cash, in real time and I will
continue to use the information with my own real cash, long after you have put the
book down. I hope you are able to take a ton away from the following pages, though
as always, please remember to trade safely and of course: common sense is king.
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Even though we're not even close to the end of the book yet, I would like to mention
that I appreciate you having purchased this book… Should I swing for the fences
[again] trading -when I'm like, 60; you sleep easy knowing you helped pay for my
room at the old folks home. I will do my best to convert the Bingo hall into a trading floor
though.
Anyway, I hope you enjoy Part Two, and please remember to keep an open mind…
Mark Whistler
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PART TWO
VOLATILITY
Illuminated
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CHAPTER SEVEN
Information Acceleration in the
21st Century and the Volatility
Paradigm
"Believe nothing, no matter where you read it, or who
said it, no matter if I have said it, unless it agrees with
your own reason and your own common sense."
~ Hindu Prince
Gautama Siddharta
What if?
What if some of the information we believe is truth…is not…
Rather, please allow me a moment to rephrase…
What if the information we believe as truth, is valid in some regard, but to us -as
traders, is not providing an accurate picture of reality within markets?
In Chapter Three, we already covered how our own memories can play tricks on us,
how media can literally recreate our perception of past events (shown in the poison
tree example), we even saw how our emotions can be cyclically altered through
headlines and media.
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What we have to understand…is that not all information is incorrect and not
information that we have might believe is false…actually is. In reality, there is another
variable happening here, which we did not touch on in Chapter Three.
See, the entire paradigm of how we (and markets) receive information has changed
dramatically over the past 10, 30, 50 and 100 years.
To understand Volatility Illuminated, we have to look into information (within
itself), in raw form, as we take it in daily.
I know the aforementioned sounds slightly cryptic, however, as you're about to see,
information has changed. Moreover, the 'speed of information' has also accelerated,
causing the critical mass of 'noteworthy distributions' to alter in look, shape, size,
smell, and impact, as well.
As you are about to see, credulous public acceptance of 21st Century information
and dangerous historical benchmarks are not only causing greater potential fallibility
and volatility within Government and markets, but in our reception, digestion and
action upon much of the information we receive daily, as well.
In the end, we will never truly understand market volatility if we do not come to a
solid understanding that present-day mass-market and public ignorance of the
contemporary 'altered information' paradigm, has created an 'explosive exponent' within
trading, politics, economics, and even sociology.
To illuminate the problematic circumstances I have just mentioned, throughout
Chapter Seven, we will see how even the major indices may be presenting unclear
information, how and why the larger information paradigm has changed, and how all
of the aforesaid is impacting markets, trading and volatility overall.
After Chapter Seven, you should:
1. See why we must question the larger paradigm of the distribution and reception
of information by market participants, affiliates and media overall.
2. Understand that often, extensive market volatility is the product of the masses not
understanding the true reality of the information they are presented, misleading
packaging of the information from the start, and overall, a significant
unrecognized change in the larger light-speed information paradigm…over the
past 100 years.
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3. See how information and markets have changed in recent years, thus, clearly
recognize why understanding volatility and probability within today's trading
environment is absolutely critical to navigating markets profitably.
4. Come away with firm clarity and understanding that those who trade purely from
technicals and/or fundamentals (retail, or institutional), without attempting to
understand the volatility paradigm surfacing in modern markets, are setting
themselves up for eventual failure.
See, populations, investors and even politicians often move in herds, sometimes
completely disregarding new and challenging information, should the information
require a change in belief structure and/or defy comfortability, career, wealth, or socioeconomic standing and status. What I've just mentioned means when there is a dirty
truth hanging over markets, the masses usually ignore the occurrence for as long as
possible. However, when the larger potentially damaging situation can no longer be
ignored, the masses will again move 'en masse', with fierce vigor. What we're talking
about is panic…
To separate ourselves from the crowd in life and trading, we must take the time to
understand why and how the information paradigm has changed. In the end, it is not
enough to simply understand volatility through traditional methods such as the
Market Volatility Index VIX (a measurement of market fear through option premiums);
we must also understand the theoretical and philosophical underpinnings of how mass
market volatility is created from the start.
Pre-Loading Major
Markets for Volatility
First in our discussion, I would like to take a moment to introduce you to what you
likely already know as a reliable benchmark of markets: The Dow Jones Industrial
Average (DJIA). As most are likely aware, the Dow is comprised of thirty of the largest
major public companies within the United States. In essence, the DJIA is an 'average' of
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thirty stocks, all with 'large cap' weighting, meaning their respective markets caps
generally exceed $5 to $10 billion.
As the Figure 7.1 shows, the DJIA is comprised of large name companies most
would recognize in a heartbeat.
Figure 7.1
On first glance, it makes sense to trust the
Dow Jones Industrial Average as a valid
benchmark to track the U.S. economy and the
sentiment of investors through the daily buying
and selling of the index. Moreover, it is also
likely fair to say that then the Dow moves up,
investors feel good about the economy and
when the Dow falls, investors feel the economy
is in trouble.
Not so fast though, there's something else
happening here that savvy traders will likely
want to be aware of.
Some argue that measuring the 'average' of
thirty stocks is not a true snapshot of the whole
economy and thus, does not accurately measure
the present-day health of all sectors and
business within the United States.
However, in our never-ending pursuit of
truth, and the true underpinnings of volatility,
we brush off the typical arguments both for and
against the DJIA in exchange for greater
understanding of a perhaps larger (hushed)
problem looming under the surface.
The problematic issue with the DJIA actually has nothing to do with the 'total
amount' of companies that make up the index… Rather, the knotty concern with the
DJIA is really in the way the index calculated from the start.
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Did you know there are basically five methods used to calculate indices? 30
They are:





Market Capitalization Weighted Indices
Modified Market Capitalization Weighted Indices
Price Weighted Indices
Fundamentally Based Stock Indices
Attribute Weighted Indices
Can you guess which of the previous five methods is used to calculate the Dow
Jones Industrial Average? If you guessed 'price weighted', you guessed correctly.
Traditionally, price weighted indexes are calculated by summing the prices of all
components and then dividing by the total. When the Dow kicked off way back in
1896, there were only 12 initial components. Charles Dow added up the prices of all
the companies and then divided by 12.
Figure 7.2
That's it, nothing to it!
Over the years, 18 more companies were added to
develop the present total of thirty components. There's
more to the story though…
The real meat to this tale is in the math behind how the
Dow is calculated…
Let's take an example where we have 10 companies in
an index:
Looking at the Figure 7.2, we see that the total of all
prices equals $355. Moreover, by taking the sum and then
dividing by the total (10), we end up with an average price
of $35.5, which would be the 'index value'.
But let me ask you a question, what happens one of the
stocks split in the index? Would it change the index value?
You bet it would.
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Figure 7.3
Moreover, given that the more expensive a stock
becomes, the more likely it is to split, unless of course,
it's Berkshire Hathaway.
For the sake of example, let us assume the most
expensive stock in our list, Company 5, splits. Instead of
calculating the index value with the previous $100, if we
made no other adjustments, we would use the post split
price of $50 in our sum of all the prices.
Figure 7.4
The new sum of $305
divided by the total (10), would
give us a new index value of
30.5, versus the pre-split index
value of 35.5.
Because of the split, the index value is now 14% lower than
it was before the split, however, nothing fundamentally
changed in the stock and really, not a single share was sold in
the whole process.
To overcome the loss in index value should a split occur, the
Dow Jones Company instituted the use of a divisor. The
divisor is calculated by taking the post spilt total of the prices
and then dividing by the original value.
For example, if we had 10 $100 stocks and one component
split, the divisor calculation would be simply to divide $950 by
the original $1000, which would give us a divisor of 0.95.
Then, to calculate the actual index, the post split sum of all
stock prices is divided by the divisor, which provides a more
accurate price of the index.
In the case of our previous example, if we utilize a divisor we would divide the postsplit sum of prices ($305) by the new divisor (0.87), bringing us back to original total of
$350. Then dividing by 10, just like in our pre-split example, we would end up with a
correct index value of 35.5.
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Thus, the divisor brings the sum of all prices (reflecting splits) back to the correct
pre-split summed value of prices…for us to then divide by the total components in the
index.
The methodology I have just shown is a Price Weighted Index.
Sounds reasonable correct?
Not so fast. There is an inherent issue with this method.
Foremost, as time passes and more companies within the index split, the divisor
becomes smaller and smaller…
Normally small numbers aren't too scary right? Wrong.
Every time a stock splits in the Dow, the divisor becomes more minute, thus
creating even more volatility within the index.
Did I just use the word volatility? Yes I did. Volatility is in fact created within the
Dow Jones Industrial Average because of the way it is calculated.
Let me explain… As of June 9, 2009, the Dow Jones Company announced: 31
The Dow Jones Industrial Average will be calculated with a new divisor prior to
the open of trading on Monday, June 8, 2009. The divisor for the Dow Jones
Industrial Average changes to 0.132319125 (from 0.125552709) as a result of
the following actions:
• General
Motors Corp. (Pink Sheet: GMGMQ) is to be deleted from the Dow
Jones Industrial Average.
• Cisco
Systems Inc. (NASDAQ: CSCO) is to be added to the Dow Jones
Industrial Average.
• Citigroup
Inc. (NYSE: C) is to be deleted from the Dow Jones Industrial
• Travelers
Cos. Inc. (NYSE: TRV) is to be added to the Dow Jones Industrial
Average.
Average.
After 113 years, so many stocks have split in the Dow Jones Industrial Average, the
divisor is now at an extremely low 0.132319125.
What does this mean to you?
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Think about it for a moment, if a stock moves up $3 in a single day, the occurrence
would add 22.7 points to the DJIA closing value for that day. ($3 / 0.132319125 = 22.7)
Let's take a moment and step back from the situation though…to consider the
'common sense' behind what's happening. If you have a $10 stock that moves $3 in one
day, the stock would have individually gained 30% in the session. However, if you
have a $100 stock that moved $3 in one day, the stock would have gained 3% in one
session.
Which is more likely, a stock gaining 30% in one session, or a stock gaining 3% in
one session?
The common sense answer is obviously that it is more likely that a $100 stock will
move $3, over a $10 stock. Thus, because of the way the Dow Jones Industrial Average
is calculated, higher price stocks within in the index have greater influence in the total
value of the index. What's more, the higher stocks move (within the index), the more
rapidly the index value climbs…or falls.
To gain the upper hand on the Dow, one could theoretically track the top ten most
expensive stocks on a daily basis for greater guidance into the indexes' potential
movement, versus just tracking the index by itself.
Why?
Think about it for a moment… If higher price stocks have greater probability of
larger price swings, and prices really have the greatest impact on the index value, it
would makes sense that we would more closely watch the stocks that see greater dayto-day price swings, over the lesser price components.
I will explain this in detail in a moment, first though, please note that as of June 18,
2009, the components (and respective prices) of the DJIA were:
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Figure 7.5
Components of Dow Jones Industrial Average
COMPANY NAME
3M Co.
Alcoa Inc.
American Express Co.
AT&T Inc.
Bank of America Corp.
Boeing Co.
Caterpillar Inc.
Chevron Corp.
Cisco Systems Inc.
Coca-Cola Co.
E.I. DuPont
Exxon Mobil Corp.
General Electric Co.
Hewlett-Packard Co.
Home Depot Inc.
Intel Corp.
Intl Business Machines
Johnson & Johnson
JPMorgan Chase & Co.
Kraft Foods Inc. Cl A
McDonald's Corp.
Merck & Co. Inc.
Microsoft Corp.
Pfizer Inc.
Procter & Gamble Co.
Travelers Cos. Inc.
United Technologies Corp.
Verizon Communications Inc.
Wal-Mart Stores Inc.
Walt Disney Co.
TICKER
MMM
AA
AXP
T
BAC
BA
CAT
CVX
CSCO
KO
DD
XOM
GE
HPQ
HD
INTC
IBM
JNJ
JPM
KFT
MCD
MRK
MSFT
PFE
PG
TRV
UTX
VZ
WMT
DIS
Index Value on June 19, 2009
PRICE
59.37
11
24.64
24.04
13.22
48.44
33.65
68.06
18.92
48.81
24.97
71.05
12.1
38.35
23.52
16.01
105.89
56.09
35
25.41
58.17
25.91
24.07
15
50.64
42.08
54.2
29.66
48.17
23.53
8,539.73
Now, in Figure 7.6, please note the 'total impact on index value' of a one-day 1.5%
gain in the top 10 most expensive stocks, over the top 20 least expensive components
(Figure 7.7).
Figure 7.6
Top 10 (Most Expensive) Dow Stocks
Company
Intl Business Machines
Exxon Mobil Corp.
Chevron Corp.
3M Co.
McDonald's Corp.
Johnson & Johnson
United Technologies
Procter & Gamble Co.
Coca-Cola Co.
Boeing Co.
Stock
Price
105.89
71.05
68.06
59.37
58.17
56.09
54.2
50.64
48.81
48.44
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One-Day
Pt. Impact
1.5% Gain
on Index
1.58835
12.00
1.06575
8.05
1.0209
7.72
0.89055
6.73
0.87255
6.59
0.84135
6.36
0.813
6.14
0.7596
5.74
0.73215
5.53
0.7266
5.49
Total
+70.37
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All things being equal, a 1.5% move up in every stock in the Dow Jones Industrial
Average would equate to a +128-point gain in the total index closing value.
Of the +128-point gain, the top 10 most expensive stocks would have contributed to
54.93% of the gain, while the bottom 20 would have contributed to 45.07% of the gain.
Ironically, the top 10 stocks moved the exact same percentage as the bottom 20 and yet
have greater 'weight' on the total index value.
Figure 7.7
Bottom 20 (Least Expensive) Dow Stocks
Company
Wal-Mart Stores
Travelers Cos.
Hewlett-Packard
JPMorgan Chase
Caterpillar Inc.
Verizon
Merck & Co. Inc.
Kraft Foods
E.I. DuPont
American Express Co.
Microsoft Corp.
AT&T Inc.
Walt Disney Co.
Home Depot Inc.
Cisco Systems
Intel Corp.
Pfizer Inc.
Bank of America
General Elec.
Alcoa Inc.
Stock
Price
48.17
42.08
38.35
35.00
33.65
29.66
25.91
25.41
24.97
24.64
24.07
24.04
23.53
23.52
18.92
16.01
15.0
13.22
12.1
11.0
One-Day
Pt. Impact
1.5% Gain
on Index
0.72255
5.46
0.6312
4.77
0.57525
4.35
0.525
3.97
0.50475
3.81
0.4449
3.36
0.38865
2.94
0.38115
2.88
0.37455
2.83
0.3696
2.79
0.36105
2.73
0.3606
2.73
0.35295
2.67
0.3528
2.67
0.2838
2.14
0.24015
1.81
0.225
1.70
0.1983
1.50
0.1815
1.37
0.165
1.25
Total
+57.73
What we're talking about here is an index that is preloaded for volatility, especially
if old market adage of higher prices over the long haul holds true. Fact is, as the prices of
the individual components in the DJIA climb, the more volatile the index becomes,
given the present price/divisor paradigm.
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With the aforementioned in mind, we can assume that the higher the DJIA moves:
1. In terms of point swings, the daily moves will be greater.
2. Media hype will only increase in years to come, as 200, 300, 400 and 600 point
swings begin to surface -daily, in the index.
3. The index has been 'artificially pre-loaded' to gain-ground.
Point number three in my last statement hopefully caused a few readers to raise
their eyebrows… I did, in fact, say 'artificially pre-loaded to gain ground.'
Please allow me a moment to clarify… In the fall of 2007, the Dow Jones Industrial
Average hit an all time high of 14,198.10, obviously before U.S. mortgage markets fell
through the floor, and before the entire financial crisis really unfolded. By June of 2009,
the DJIA was down about 40% from the 2007 high.
Funny thing though…if you remember the divisor announcement a few pages ago,
we also know in June of 2009, two stocks were removed from the index, and were
replaced by two new companies.
The announcement read:
• General Motors Corp. (Pink Sheet: GMGMQ) is to be deleted from the Dow
Jones Industrial Average.
• Cisco Systems Inc. (NASDAQ: CSCO) is to be added to the Dow Jones
Industrial Average.
• Citigroup Inc. (NYSE: C) is to be deleted from the Dow Jones Industrial
Average.
• Travelers Cos. Inc. (NYSE: TRV) is to be added to the Dow Jones Industrial
Average.
Let's take a moment to consider the reality of the situation here… In October of
2007, General Motors posted a relative high of $41.93, while Citigroup tagged a high of
$45.09 in the same month…
By June of 2009, General Motor's stock was trading at $1.75, while Citigroup was
trading at $3.17.
In all, from October of 2007 to June of 2009, General Motor's stock lost 40 points (95.8%), while Citigroup had peeled off 42 points (-93%). Here's the thing though, if you
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remember our discussion a moment ago about the DJIA being 'price weighted', using the
pre-June 9, 2009 divisor of 0.125552709, the total point declines of General Motors and
Citigroup contributed to 653 points of the 5,658.37 points lost in the DJIA, since the
October 2007 highs.
So how would the Dow ever climb back to a level where media and investors would
ever pay close attention to the index again, if Citigroup and General Motors stocks are
likely to stay under $10 for a long, long time? What do you think the solution is?
General Motors and Citigroup were 'black eyes' for the Dow, and considering it is
much, much tougher for a $40 stock to add $10, versus a $100 stock, both stocks were
poised to remain as major drags on the index for years.
What I'm saying is if a few of the stocks in the index have been beat up considerably
(like fallen under $10), wouldn't the occurrence make it much harder for the Dow to
ever post new highs again, with the cheaper stocks weighing heavily on the total index
value?
You know it.
Dump the losers and replace them with stocks that have a better chance of gaining
ground. The higher the new stocks climb, the more points they will add to the total
index value.
Bingo! General Motors and Citigroup were kicked to the curb and replaced by
Cisco and Travelers.
Fact is, as of June 9, 2009, because Citigroup and General Motors were booted from
the Dow, the index now stands a greater chance of recouping losses (and eventually
making new highs) than if the flailing bank and auto manufacturer were still a part of
the benchmark index.
When the Dow eventually climbs back to new highs, media will likely tout 'the bull
is back' or something like 'you can't keep the Dow down' (or whatever), however,
media will likely forget to mention the mega-money center bank that was replaced by
a property & casualty insurance company and the 'American as apple pie' automanufacturer that was replaced by a network and communication devices company.
What's more, when considering that there's no longer any auto-manufacturers in the
Dow now, it seems awkward to assume the index truly reflects a fair breadth of
products used in the calculation of consumption and GDP growth – in America.
At the end of the day, if every time the Dow pulls back in an economic hiccup, 'beatdown' stocks are replaced by others that hold greater potential to ascend, the event
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really means the index will likely make new highs (again) in the years to come, but not
truly reflect the American economy, as it is said too.
Analysts will continue to tout 'the investor who bought Dow stocks and held them over
the past fifty years has seen his portfolio continually climb, even with the crash of 1987, the
dot.com bomb and the financial crisis.'
But what they won't tell you is part of the reason the Dow is able to keep making new
highs –decade after decade– is the lesser performing components are dumped like a bad
date, any time the kitchen gets hot.
Eventually, the Dow will hit new highs and day-to-day volatility (in terms of price
swings) will be greater than ever. Really, we're talking about preloading volatility into
markets.
In a few years, when the Dow is back at highs… Citigroup and General Motors will
likely still be in the gutter trying to recover.
There's even more to the story though…the volatility story, I mean… As I've just
pointed out, the way the DJIA is calculated (and preloaded) is all geared to help the
index constantly make new highs over time. New highs mean new press and new
press means more exposure. It's about maintaining 'benchmark status', while keeping
investors interested in…investing. However, much like our memories are easily
influenced by media (in recollection of historical events) the Dow example is another
instance of 'important information' completely passing by the general public. Given
the larger financial crisis, political events of the day and everything else one must
constantly worry about, why would the calculation of an index ever even be important
to take note of? What we're really talking about is the total mass of information
required for investors to truly stop and mark as important. In the 21st Century
information paradigm, unless an event has enough 'sauce' to spark significant fear
(loss) or exuberance (greed) within individuals, the information passes like a shooting
star on a cloudy night. Eventually, the DJIA will likely hit new highs and media will
again gawk and squawk about the event, thus sucking investors into the poison tree
(yet again) and of course, eventually the economic cycle will take a downward turn and
those same investors will see their wealth decrease, as major indices take another
nosedive.
I'm not saying that we shouldn't invest…after all, now that the DJIA has been
'reloaded' for possible upside, the present day actually appears to be a decent time to
buy…at least if the U.S. Dollar doesn't plummet in the near future, due to the loss of
credit quality of U.S. Treasuries, based on excessive spending by the Government…but
that's another conversation.
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The point, however, is we can certainly invest in markets and indices, so long as we
are fully cognizant of the volatility paradigm. Moreover, we must also recognize that
the larger problematic issues behind how the delivery and reception of 'information'
has changed in the 21st Century, while actively seeking out information that could
present future volatility – ahead of time.
As many readers may still be a little unclear about the larger shift in the 'information
delivery and reception' paradigm I keep mentioning, we will now cover 'why' and
'how' the aforementioned has changed and what it all means to markets and volatility.
Over the next section, we're going examine Einstein's Theory of Special Relativity
to see how information has changed and at the same time, how such impacts markets.
However, please do not feel that you need to work through the math; really, the
most important part is to simply just make sure to take the time to understand the
philosophical and theoretical underpinnings (as pertaining to markets and volatility)
behind the physics.
Market Volatility through
EINSTEIN'S THEORY OF SPECIAL
RELATIVITY
I'm sure many readers are wondering how Einstein is relevant to markets and
volatility… Moreover, those who aren't too fond of math likely already have their
fingers into the next chapter, ready to skip over the following pages at the first sign of
big brainwork. However, please know what we're about to cover is very important in
the larger understanding of macro market volatility and how individuals, professionals
and markets collectively receive and act on (or discard) critical information.
As we are about to see, information actually does have 'mass' and with the
technological innovations of the past few decades, the overall formula behind the
energy of information moving markets has changed.
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What I'm saying is because information is now moving at the speed of light, market
volatility is increasing (and will likely continue to swell), as the larger populous is
progressively more inundated with even more information… Moreover, as the masses
continually become exceptionally trusting of, and more dependent on media, while at
the same time (and unfortunately), gradually more neglectful of taking the time to
personally seek out 'real information' about to impact their lives…
As you're about to see, the 'postmodernism' of market moving information is a
troublesome condition of 'see no evil, hear no evil, don't want to deal with any evil',
causing markets (especially Forex) to present more and more volatility (seemingly out
of the blue) every day. Moreover, because the masses prefer to turn their heads at
information containing real warnings within markets, when bad news can no longer be
ignored, markets tumble…fast.
Don't be discouraged though…because as long as you're willing to see information
and markets clearly, you're one of the few…now 'in the know.'
We will begin our discussion of physics and the larger 'light speed information'
paradigm with Einstein's Theory of Special Relativity, taking special notice of Mass
Energy Equivalence (E = mc2) and Length Contraction.
As a quick side note, E = mc2 is not 'the' Theory of Relativity, as many believe…
In reality, E = mc2 stands for Mass-Energy Equivalence and is one of four
derivatives from Einstein's 1905 paper: Zur Elektrodunamik bewegter Körper (On the
Electrodynamics of Moving Bodies). 32
The aforementioned paper attempted to define the structure of spacetime, via
Special Relativity.
Spacetime (as a loose definition) is a mathematical model, or theory attempting to
mold space and time into one continuum. 33
While E = mc2 is not the core concept I am presenting here, the theory of MassEnergy Equivalence and Special Relativity do have a few points we should note in
terms of information in the 21st Century, financial markets and volatility.
Just as a quick primer, within the Theory of Special Relativity, we find four major
consequences:34
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→
Relativity of Simultaneity: Two events, simultaneous for two observers, may
not be simultaneous for the observers, if the observers are in relative motion.
→
Time Dilation: Moving clocks should theoretically, tick more slowly…than
an observer's "stationary" clock.
→
Length Contraction: Objects in motion, as measured in relative width from
the stance of an observer, will shorten…in the direction they are moving with respect to
the observer.
→
Mass-Energy Equivalence: E = mc2, energy and mass are equivalent and
transmutable.
Quickly walking through each of the four points of Special Relativity:
1. When examining Relativity of Simultaneity, at some level the theory holds true
within markets, as the overall concept tells us that simultaneity is not absolute, rather is
dependent on the observer's position.
2. Time Dilation means the faster something moves, the more time slows down for
the thing in motion. If you were standing on earth and you could see a spacecraft
moving on the other side of the universe, and it was/is moving at the speed of light…
In fifty years of your life, the spacecraft might cover 30 percent of your visible sky.
However, for the people in the spacecraft, because they are moving at the speed of
light, in the same fifty years, they would have aged significantly less. What the theory
is saying is time is relative to the location of the clock; in other words, time is relative to
frame of reference.
What the theory is also implying is without another reference point, time will
remain constant. The issue here (with the way the Dow is calculated too), is we do
actually have a constant frame of reference, by which we base time off of, derived from
the simple fact that none of is moving (or has moved) at the speed of light (or even
remotely close to it) anytime in the past 100-years. (And likely since the beginning of time,
unless there's something I'm missing.)
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Here's something to consider though… In 1909, a devastating press release
sometimes took days (even weeks) to reach the investing masses, given the lack of mass
communication, as seen today. Let's say, for example, it's 1909 and in your previous
life, you were JP Bigwig…and you controlled a massive position in coal all across
America, especially in the Appalachians.
While you're in Canada fishing, a freak earthquake hits your largest coal
investments, devastating production.
Because it is 1909 –and you're in the woods fishing, your team can't exactly call you
on your cell…
See what I'm saying?
In modern markets though, information travels exponentially quicker (and more
efficiently) via fiber optic cable, satellites, television, cell phones, and Internet...
The speed of information has increased, though time is still the same as it was in
1909. Consider what's really happening…information is (literally) now traveling close
to 300,000 kilometers every second. How fast is that? If I were light, I could circle the
globe seven times in one second; or about 28 times, in the four seconds (by my
estimate) it is taking you to read this sentence.
In 1909, information often traveled at the speed of old Jeb and his sidekick in the
wire-house. Jeb got the wire and then told some kid to run around and tell others. The
kid's name was Flash.
Humor aside, what we have to understand, is because the information has increased
in speed, while time remains constant, the occurrence has changed the 'mass' element
of market moving information, and thus, is causing increased volatility within
markets. A few physicists might argue with me, but they don't trade with real cash
every day, watching how events impact markets every second… From the laboratory
of the trading floor, the empirical evidence shows information is moving so fast, most
slips by unnoticed, until the mass is just too big to ignore.
As I am about to show, the theory of Length Contraction will provide us with
some proof that that 'mass' of information has changed. Then, later in the chapter, I
will show how volatility (through the mass and speed of information) has increased
overall, by examining major historical moves in the Dow Jones Industrial Average over
the past 100 years.
Again, what we have to understand is because information is now moving at the
speed of light, another variable within relativity absolutely must have changed. The
variable I am speaking of is the larger ignorance and passivity of society, through
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complete inundation of information, whereby information is ignored until the total
mass of such threatens critical impact, either through fear, or exuberance.
Figure 7.8
3. Length Contraction means the faster something moves, the more it compresses
in relation to the observation of a stationary viewer.
Figure 7.9
Take a moment to glance at the image of Mr. Stick
Trader (Figure 7.9), though please don't laugh at my
artwork! In the theory of Length Contraction, the faster
an item moves in relation to the observer, the more it
will compress.
In context: For a stationary individual or securities
trader for example, the little black box moving from left
to right (in the image above) is slightly more than three
times the width of the stick figure's head.
Now, look at Figure 7.10 on the following page…
If the little black box accelerates to 85% of the speed
of light, the box would appear only about one and a half times wider than the head of
Mr. Stickman Trader.
Here's where the story gets interesting… Consider that perhaps the 'thing' is
information.
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Figure 7.10
In the early 1900's, when the Dow Jones Industrial
Average was just getting off the ground, information
really only traveled by wire and/or telephone. For
example, in 1906, the telephone industry put in a recordbreaking achievement completing the first-ever longdistance underground line call, totaling 90-miles from
New York City to Philadelphia.35
Today, however, information moves much, much
faster… Case in point, information virtually moves at the
speed of light through fiber optic cable.36 Fact is, in our
world, information travels 40,000 miles into space and back creating, "a pause of about
half a second between speaking on a transatlantic phone call or live television link and your
voice reaching the listener."37
Because the speed of information has accelerated dramatically over the years
(traveling at the speed of light today), in context of Length Contraction, the increase in
speed of information means the total breadth (mass) of information has shrunk.
Let me rephrase that, because information is passing by so quickly each day, the
amount of time we pay attention to information (because the mass of passing
information has compressed) has decreased. What I'm saying is with more information
passing through our perceptions daily, information is here today and gone tomorrow,
with the public quickly forgetting whatever just passed by our consciousness. We
quickly forget, or simply fail to take notice of information –until– the information has
so much mass, the game changer can no longer be ignored.
Again, if you are still standing in the same place and information has accelerated,
what is it that has changed?
Mass changed…
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Critical Mass and Conscious
Unawareness
For the public to take notice of any information as 'significant', the information must
have substantially greater mass today, than in historic years of the markets. In reality,
what has changed is the total deterioration of the general public's memory of
yesterday, active cognizance of today and even more worrisome, any thought of
tomorrow, based on the speed of information in today's Internet world.
In plain language, with information moving so much faster today, whatever the
'take notice' event is, it unfortunately must be a whopper to stick. Unless the
information contains some sort consequence to our immediate life, the information is
quickly forgotten (or ignored) all together.
Though I believe your memory is better than most, please simply state what you ate
for lunch one week ago from today? [Don't worry, I can't remember either.]
I will cover the larger populous-oblivious paradigm in detail in the next chapter.
Moreover, I will show exactly why and how the speed of information is not only
causing the average individual to become less aware of social veracity within business,
politics, and community, but also why and how the occurrence has triggered an
epidemic of volatility within financial markets.
What we must understand for now though...is perhaps the global financial crisis has
less to do with credit, mortgages, and lack of regulation, than most believe.
In essence, the ugly economic matters at hand are truly about rapidly passing
information overlooked by the public daily. Furthermore, with major media constantly
promoting fear and gloom (such was true before the financial crisis too) most
individuals protect their sanity by simply disregarding negativity.
The problem though, is as a society, we have manufactured a condition where all
warnings of pending disaster (to the global economy based on the non-existence of
credit swap regulation, for example) are completely ignored unless the walls totally
start crumbling.
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Concerning the present financial crisis, in the years just before the entire debacle
began, the public acted just as it should, turning cheek to the potential global credit
clutter looming, to protect the fragile emotional state of modern acceptance-based
socio-economic egocentricity, all fueled by the increased speed of information within
today's reality.
What I'm saying is this: Who cares about some credit issue a thousand miles away when
we work 10 to 12 hours a day, only to then run around all evening in a frenzied state of chic
productivity too?
Think about it, with so much information to take in each day, how would the
average Joe even have known to take notice of the credit-based warnings surfacing
from tenured professionals (prior to the entire global financial meltdown) anyway?
Because the average Joe and Josie are as busy as heck and completely bombed with
information all day, there is simply no way he or she can even take in all of the
information presented in the first place. And, because modern media attempts to make
every single little story a huge ' bombshell', the average person has virtually no way to
distinguish the really important information they should be taking notice of, over the
constant media fear and exuberance clutter. Therefore, he (or she) picks what matters
most…
We pay attention to now and five minutes from
now…at least…until a cataclysmic bolt from the blue
completely rocks all of our lives collectively.
It's important to also note Newton's Laws of Motion apply as well, specifically in
relation to force. As measured by Newton's Second Law of Motion, force = mass *
acceleration.
What this means is we will also need to measure 'acceleration' in terms of the verve
of information within today's marketplace.
As you are about to see, we can theoretically model Einstein's theory of MassEnergy Equivalence (E = mc2), deriving some semblance of energy needed to account
for 'acceleration' within the force required to move markets.
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In understanding the theories here, readers are about to gain some incredible
insights into the truths behind volatility, social passivity, information
purpose/deployment, speed and financial market reactions to global events and
media... Truths many may have never even thought possible.
4. E = m c2
E = the energy
m = mass
c = the speed of light in a vacuum (celeritas),
(about 3×108 m/s)
In terms of Joules: 1J = 1 kg * m2 * s-2
Just in case you're wondering:
Walking speed - 15 mph
Bicycling speed - 23 mph
Airliner cruising speed - 625 mph
Speed of sound (at sea level) - 761 mph
Speed of light - 670,616,629 mph
However, because information has increased in speed, are we now in a state where:
E = m((∆si+∆ki)/c)2
Where…
E= Energy (Volume)
m = Market Cap
∆Si = (Si) Change in the Speed of Information
∆Ki = Fear/Acceptance of Information Presented (Measured through option
premiums, or the Market Volatility Index VIX)
c = the speed of light in a vacuum (celeritas), (about 3×108 m/s)
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While the above formula is not meant to be a precise model of physics, the theory
behind what I am saying is:
Volatility is, in essence, a measurement of energy, in relation to mass and speed, in terms of
information.
It is arguable then, that the greater an item's mass, the more energy it takes to create
and sustain speed, in a circumstance where resistance prevails. In the case of any
financial product, there's an old cliché that we can use to help understand volatility a
little more…
"No one ever has to buy, but they do have to
sell…sometime."
What we're really talking about here is the amount of energy needed to keep a stock,
currency, option, or futures contract at any given level. With the absence of buying
incentive/pressure, all instruments would eventually fall to zero.
Again, Newton's three laws are:38
1. Every object will remain at rest or in uniform motion in a straight line unless
compelled to change its state by the action of an external force.
2. Forces produce accelerations that are in proportion to the mass of a body
(F=ma).39
3. Every action of a force produces an equal and opposite reaction.
For the purposes of this book, what we're rally examining in terms of volatility rests
within law #2, whereby we know Force equals mass times acceleration.
Simply put, the heavier an object is, the more force one must exert to 'start the ball
rolling', or stop the boulder from tumbling.
Like the major indices were putting in all time highs in 2007 (as the general public
just stood by and ignored the totality of the dangerous credit situation growing, which
was also seemingly 'implausible' by mainstream media that was clucking about, while
touting new highs daily), when the larger 'mass' of the global credit hydrogen bomb
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could no longer be ignored, the same media and public all panicked at the same time
(October of 2007) and en masse, tumbled markets over a cliff.
Even the credit rating agencies played there part too, as seen in Moody's downgrade
of AIG on October 3, 2007, precisely the 'panic' catalyst required to sweep the legs out
from underneath the Dow and drag the index under critical support of 10,000. 40
What we're talking about is the point of unsustainable information (mass), where
even media, credit ratings agencies and investors must finally come to grips with the
reality at hand.
Henceforth, buying energy (in relation to exuberance and/or conscious ignorance
by the larger public to truly understand economic circumstances) is more difficult to
sustain than selling, based on the logic that investors have to sell sometime, but they
never truly have to buy.
What we have is a 'gravitational effect', which tugs hard on stocks, currencies,
options, or futures the higher they travel in a defined timeline. In addition, much like it
is much more difficult to push a boulder up a hill, than down, the larger the boulder,
the greater the possibility of excess volatility when the mass becomes too heavy to hold
up, or the general public is no longer able to coherently understand the information at
hand.
Remember our conversation about consumer sentiment and inflation in Chapter
Three. It's no wonder the average Joe wouldn't even know to be on the lookout for
inflation, as he or she, likely hadn't studied the saturation principles of money supply
and were really only basing their opinions on the junk media was touting at the time…
Moreover, in December of 2008 and January of 2009, mainstream media were more
focused on deflation, than inflation.
In terms of our previous discussion of Length Contraction, the little snippets of
information (the clues to upcoming rallies, or pending panics) pass by seemingly
unnoticed because information is now moving at the speed of light. However, when a
piece of information finally passes by that is so large that it can no longer be ignored,
the masses, media, analysts, politicians and credit ratings agencies act on the
information in one large herd of lemmings…over a cliff…
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The Tipping Point of Information
Mass
As stocks, currencies, options and even futures rip through the roof, all are (as a
metaphor) traveling into the atmosphere, like a rocket. The further the rocket moves
from the earth, the less gravity 'weighing' it down and thus, the acceleration becomes
more torrid. (Have you ever noticed the fifth wave in Elliot Wave Theory is generally
always the steepest?) A stock can never totally escape the forces of gravity, though we
can admit that momentum begets momentum. Much like the upper echelons of our
atmosphere, even though gravity eases as the object seemingly 'breaks free' (almost
mass-free from the perception of investors), other factors begin to come into play.
For instance, the higher a financial instrument travels, the greater the 'risk premium'
in terms of fair valuation, seen through financial ratios.
Eventually, once the last fool is in, buyers mysteriously dissipate, seemingly
overnight. However, in the final stage of 'rocket gains' just before the stock runs out of
fuel, media hype and investor exuberance was likely at its greatest.
Really, no fuel contains as much octane and/or potential horsepower as exuberance.
Much like nitrous fueling a hot rod in a street race though, the power unleashed often
tears apart the motor at the same time.
When the last bull realizes he's nothing more than a sucker, suddenly the 'mass-free'
paradigm shifts and investors suddenly see the situation in true light for the first
time… Where mass was previously ignored, suddenly it is apparent that the moon is
seemingly crashing through the atmosphere…but investors have nowhere to hide. The
object now colliding with reality is too big.
When the 'rocket like run' is out of fuel – media yells fire in a crowded movie theatre
and the masses pile on top of one another in an attempt to all escape at the same time.
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There's another factor that plays in here too:
Conversion.
A few moments ago, I said the greater the mass of an object, the more energy
required to 'get the ball rolling.'
There's a conversion factor here we have to consider. As we know, most financial
instruments do not start out as large, or mega-cap companies. Metaphorically, small
cap stocks are like baseballs, while large cap companies are like bowling balls.
Image this: I hand you a baseball and a bowling ball and ask you to throw each as
far as you can. Which would you be able to toss further? A baseball of course. What
if; however, the baseball was actually 'magical' and as it was in the air, shifted shapes
into a bowling ball?
In reality, baseballs and bowling balls are static matter; however, financial
instruments are not. The higher a stock, currency, option, or futures contract travels,
the more it expands, adding mass. In the case of a stock, we can measure mass
accumulation through market cap growth. If shares outstanding remain the same, as
market cap grows, so must price.
There is an equilibrium point though, where the stock (via earnings per share) can
no longer sustain itself, and thus plummets back to earth, like a rocket with no fuel (the
absence of buyers.)
Where all of this leads us to is simply a question of energy required to sustain
altitude, like a satellite. The issue is that unlike a satellite orbiting earth, stocks can
never escape the gravity of earnings expectations, the reality of returns, and of course,
larger economic cycles.
Currencies are bound to GDP and expectations for GDP growth, inflation and of
course: interest rates.
Should a currency travel too high, the occurrence could negatively influence a
country's trade balance, whereby an overvalued currency will eventually trigger a
trade deficit and thus, negatively affect GDP.
What's more, when trade deficits drag out for significant periods, not only will the
occurrence hinder GDP growth, but often lead to increased national debt.
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The conversion tipping point of a currency is when the country's national debt is
seen as 'unsustainable' by foreign lenders, and thus the currency plummets, as credit
quality deteriorates.
Central banks supposedly act as a mechanic/driver to currencies, adding or
subtracting fuel (via interest rates and other open market operations); much like a
balloon-driver does propane to a hot air balloon.
However, what if the balloon driver was either an idiot from the start, or is/was
really taking orders from someone who would profit from the balloon plummeting?
Either way, the absence of competent, honest, reality cognizant balloon drivers
(non-lobbyist/media influenced, not seeking personal prosperity, beyond ego-driven
and/or not disgustingly greedy individuals, policymakers, politicians and corporate
executives) means the whole experience is going to be one hell of a rough ride
(volatility.)
Think of the occurrence as an equilibrium point within Forex markets, where a
central bank must know how to apply heat to keep the balloon from sinking too low (or
rising too high), while also understanding that when used incorrectly, the flame could
catch the entire balloon on fire.
If the balloon driver were competent from the start, the balloon wouldn't be on fire right
now.
Examining another instrument, options, on the other hand, can be measured in
terms of 'expectations of volatility', as seen through option premiums.
Option floor traders are very, very smart fellows – and in my option, are some of the
savviest of all traders (of course with the futures guys too), as they understand
profitability is more about buying and selling volatility, than tumbling in on the
directional hype bandwagon of fear, or exuberance.
Option traders get it…that trading is about volatility, not directional fear, or greed.
Option traders profit by selling the probability of credulous investors feasting on
poisonous fruit…over and over and over.
So where am I going with all of the aforementioned?
Foremost, to truly profit within equity markets, options, Forex, commodities and
futures as individual investors we need to wake the hell up, stop buying into media
hype (because they don't really know anyway), stop ignoring smaller snippets of
critical information passing by at light speed, and above all, start looking at markets in
terms of volatility and probability.
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We must start looking at markets in terms of speed (information), mass
(distributions), and acceleration (expectations).
The Dow Jones Industrial Average stands a much greater chance of recovery today,
now that the two worst performing stocks have been replaced with seemingly healthier
components.
But has anything really changed within the economy?
No.
However, as the Dow gains ground again, media will tout recovery. But the index
didn't really wait patiently for the recovery of the two worst performing components,
rather, General Motors and Citigroup were just replaced like burnt fuses in the index.
What we're talking about is pre-loading markets for volatility, by sweeping the ugly
dust under a rug.
But the dust is still there and so are Citigroup and General Motors, which
collectively employ over 500,000 people.
If (and when) the Dow rallies again, most investors will plop cash into markets
(while media touts recovery), completely unaware of the fact that all of the index
components didn't really 'recover'.
Fact is, two companies that are STILL thought of major U.S. economic contributors
(though potentially holding index down in the future) were quietly discarded in the
night, like a mobster does a dead body.
None of the aforementioned means we can't profit handsomely from markets in the
future, we just have to be aware of the situation unfolding now.
We have to understand that because information does have a tipping point (as do
markets), and because most information surfacing through media is most often wrong,
(with the real market-moving catalysts ignored), we must stop paying attention to
media hype and start paying attention to volatility and probability. In the end, by
waking up to the true mass-credulous, media-suckered paradigm of today, while also
paying attention to volatility and probability, we can finally transcend the larger 'masspopulace ignorant of light speed information' paradigm now facing investors in the
21st Century.
Now, please take a moment and look at Figure 7.11, which shows the three largest
declines in the Dow Jones Industrial Average from 1896 to 1909… As readers will
likely immediately recognize, the index experienced some whopper declines during the
previously mentioned period.
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Figure 7.11
If we take note of the major declines at the start of the 19th Century, there are a few
major points we can learn from. First, big drops in the Dow (and market) aren't new…
Selloffs happen.
They happened when the Dow first began trading and they happen now. The
second point; however, will need a little more explanation.
Figure 7.12
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* I've included 1946 and 1998, which showed similar characteristics of typical
historical bear market selloffs
Readers may have also noticed that I annotated the 'total time of selling' for each
relevant decline. Please also now take a moment to glance over the next table I've
prepared (Figure 7.12), which shows every major decline in the history of the Dow
Jones Industrial Average, which exceeded 20%.*
Over the past 100-years of the Dow, we can break trading action up into four
periods, each with their own 'characteristic' paradigms:
1896 to 1929: Industrial Revolution economy.
1929 to 1961: Post Great Depression American economic growth market,
characterized by "middle game" industrial development and The Securities Act of
1933.
1961 to 1981: Baby Boomer's come into their own entering colleges and taking
positions in workplace. Era characterized by mass acceptance/distribution of
televisions, and thus, the initial birth of the 'light speed information' paradigm, as
noted in 600 million American's having watched Neil Armstrong become the first
man to walk on the moon, on July 21, 1969.41 Era also included the invention of the
personal calculator (1966) and the release of the first consumer computers (Scelbi &
Mark-8 Altair and IBM 5100 in 1974 and 1975).
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1981 to Present: Technology Explosion Market.
In the popular Website How Stuff Works, writer Marshall Brain lists 12 major
technologies of the 1980's as:42

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Personal computers
Graphical user interface
CDs
Walkmans
VCRs
Camcorders
Video game consoles
Cable television
Answering machines
Cell phones
Portable phones
Fax machines
Here's some interesting information not readily in the minds of most…
In my second book, Trade with Passion and Purpose (Wiley, 2006), I had the
wonderful experience of interviewing Joe Ritchie, whom some may recognize from
New Market Wizards, by Jack Schwager. I won't ever forget the time I spent
interviewing Ritchie, which was really a series of conversations over about two
months. Ritchie is truly one of the greatest market innovators of all time, as one of the
very first to computerize option valuation and merge the information into his firm's
trading on the floor of the CBOT. During the 1980's and 1990's, Ritchie's firm Chicago
Research and Trading (CRT) took over $1 billion in trading profits out of markets.
I also interviewed Ritchie for my column in Trader Monthly Magazine, which
unfortunately, has gone out of business with the global financial crisis.
In my interview with Ritchie, he referred to traders on the floor of the CBOT (in
1977) with programmable calculators, as instantly becoming, "a one-eyed man in the
land of the blind."
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With everything mentioned in over the past few pages in mind, my point is that
while technology has indeed progressed over the past 100-years, so has Wall Street's
ability to act on, and react on information…
However, traders and firms who are now truly technology to benefit in day-dayday market activity are rare. Though the average investor believes he, or she has
'greater insights' into markets with their supercharged trading platforms, I believe the
exact opposite is really the case. Really, average investors of today are less savvy than
100-years ago, while really, having just become nothing more than media induced
volatility-conditioned chimps. I'm even talking about intraday retail Forex traders who
think they're savvy chartists.
Case in point, remember our recent discussion on CCI? In one of my recent
Webinars, I asked the room of traders (about 40-people) what CCI indicated… The
ONLY answer I received was 'overbought' and 'oversold' above or below +100 and 100, respectively. Not ONE of the supposed serious traders knew what CCI really was.
I don't mean to be rude and I hope I don't sound like I'm attempting to be.
However, what I'm saying is, 'what the heck are overbought and oversold' anyway?
I'll tell you what they are…Overbought and oversold are the explanations of CCI
presented to the masses by 99% of market-information Websites out there…
Chimpanzees beget chimpanzees.
To break this devastating trend, we must look beyond the commonplace
explanations of indicators and trading served to the public daily.
Moving on, to the below table of major declines in the Dow Jones Industrial
Average (shown again), I would like readers to take serious note of final column on the
right labeled 'Avg Time'.
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Figure 7.13
What I would like to point out is that the average duration of bear markets has
decreased by nearly 60% since the 1901 to 1929 market. What's more, if we take out the
larger total bear market from 1999 to 2002, bear markets in the past 20 years have only
lasted about a quarter of the time that they did in the past 47 years. $
$ -Note- The historical average PE ratio for the Dow Jones Industrial Average is 15.5 (since 1929). In early 2002,
despite dot.com bomb selling, the index still had a PE of 25, thus overvaluation contributed to the longer than usual
bear market. Index changes in 2009 instantly lowered DJIA trailing PE from 21.21 to 11.41, while also dropping
forward PE from 18.06 to 12.80, thus setting the index for a future run into (approx) 11,500, or a 15.5 historical PE.
What we can assume – over all - is bear markets, though totaling 'about the same' in
terms of percentage loss, are accelerating in duration.
Why?
Because fundamentals improve quicker today, over 75 years ago? No…
Duration of sell offs has decreased in total time, because through the acceleration of
information, collectively, investors have a much narrower memory of yesterday, with
media constantly pumping exuberance through television, Internet and radio the
second the economy shows signs of recovery.
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What's more, take into consideration the fact that the Dow Jones Industrial Average
has now been 'reloaded' for volatility, the second the index fires over 10,000 again; the
occurrence will become headline news… Guaranteed.
Will you buy into the volatility?
Information has accelerated, and thus our memory of yesterday has declined, while
at the same time, the collective public's ability (and desire/effort) to take notice of
important micro-information (that could have major impact on the future) has
decreased.
What I'm saying is… Not only have markets become more volatile (as noted in the
increase in total time of DJIA bear markets); but speed and volatility of intraday and
longer-term market changes are only going to increase even more in the years to
come…
The fact that 99% of the investing public has no idea of events like the DJIA having
been re-loaded for gains is proof of the pudding of the general public's microinformation mass ignorance, with your old pal 'media' doing nothing to bring you the
real truth behind the events of today… At least, until some sort of underlying hum
within markets can no longer be ignored, and the major indices are crushed once
again…
Perhaps something like the United States' National Debt of $11 trillion (FYI, foreign
investors owned $3.47 trillion of public debt, at the time of printing), the potential pending
deterioration of credit quality in U.S. Treasury notes…and the implosion of the greenback.
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CHAPTER EIGHT
Volatility and Probability
through the movement of
Distributions
Over the following pages, we will focus on
volatility and probability in terms of Forex markets;
however, the concepts also apply to equities, options,
commodities, and futures. As many traders are
already aware, Forex markets often display
significant volatility catching many participants by
surprise. However, with a simple understanding of
descriptive statistics, traders could soon find
themselves ahead of the curve.
Many traders – both new and experienced – often
find themselves at a loss attempting to understand
why Forex markets tend to experience extended
volatility both intraday and over the long haul. In
simple terms, much of the seemingly erratic moves
are really the product of institutional order flow,
causing larger movements within markets. While the
aforementioned explanation is almost infuriating
simple, we must understand, large money is really the
pure catalyst behind extended movements within
markets, not at-home investors. We can argue that by
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acting in unison on common technical signals, the mass army retail investors do indeed
add to the issue of erratic volatility within markets. However, volatility caused by the
retail community is 'quick-shot' volatility at, or near areas where commonplace
technical signals (like Stochastics rolling under +80, for example) unfold. What's more,
quick-shot volatility caused by retail traders is not 'trend sustaining', as really,
institutions are the only entities with enough buying or selling power to prolong
trends.
Moreover, the individual investor is often set up for failure from the start, because
not only is he or she not able to 'see' institutional order flow (imagine the ticker tape in
equities), but because traditional 'pre-loaded' information he/she is receiving is often
'missing' critical components, all at the same time.
The question is then, how can traders transcend failing technicals, increasing
volatility and jaded information, to achieve greater insights and perceptions into
serrated movements within Forex.
In other words, "How can we perceive volatility before it occurs?" Over the
following pages, I will attempt to explain how using principals of descriptive statistics
can help identify trending and reversals, while also foreseeing volatility within almost
any charting timeframe.
In the end, we will break through market volatility with a greater understanding of
the dynamic movements of subset distributions, while also utilizing common
probability within descriptive statistics to capitalize on market action.
It is important to note that even when traders embody substantial technical and
fundamental knowledge, risk prevails without the proper understanding of the larger
probability and volatility paradigm behind currency trading.
Here, traders are encouraged to boldly challenge typical pre-conceived notions of
technical and fundamental analysis, in an effort to see beyond 'the accepted standard'
retail traders are told to believe daily. The 'accepted standard' does not presently
uphold volatility and probability as important aspects of markets or trading. However,
given that 80% to 95% (depending on who you talk to) of retail Forex traders lose,
while many retail brokerages actually take the opposite side of their trades, perhaps the
at-home trader isn't supposed to know anything more than the 'accepted standard'.
Traders who understand descriptive statistics though, will find greater clarity and
perception of volatility within intraday and longer-term movements unfolding in
markets.
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Words of Caution
 Within Forex and trading, there is no holy grail; thus, please do not read the
following with the firm belief that you will never again be faced with
confusion, unclear volatility, or losses in markets. What you are about to learn
is an incredibly effective guidance tool helping identify trending, volatility and
at times, reversals; however, even the concepts here must be used with
prudence and common sense.
 You are about to read about descriptive statistics, which within itself has many
different approaches, methodologies and studies. I will not delve into the
justification of math underneath most statistical concepts here. Instead, I am
presenting descriptive statistics from a simple, conceptual framework.
However, there are many resources available to explain the empiricism of
descriptive statistics on the Internet and in your local library; you will also find
plenty of recommended reading in the bibliography at the end of the book,
should you chose to learn more about the subject (which I highly recommend).
 Never forget that economics and fundamentals rule all…at least, over the long
haul. Traders who do not take the time to properly uncover the true economic
paradigm within markets –and the future possibilities of such– will likely often
find themselves on the wrong side of the trade, especially those who hold
positions during longer timeframes. While the concepts presented within
Volatility Illuminated are designed to specifically help traders navigate intraday
movements and volatility within markets, we have no excuse to ever slack on our
fundamental research. Please take time to do the proper research every day.
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Transcending Markets through
Volatility and Probability
Almost all financial markets display relentless volatility for traders attempting to
capitalize on trading within shorter-term timeframes. Intraday uncertainty and
volatility are just facts of trading in virtually every market. Moreover, because of the
inherent underlying "volatility paradigms", many traders (both new and seasoned)
stand significant risk of unforeseen losses, almost any moment their positions move
against intraday order flow.
In Addition, while order flow may not seem like a reasonably transparent variable
in Forex, in reality, through descriptive statistics, we may not only predict when and
where institutional order flow could commence, but where such could end as well.
In the end, through volatility and probability, savvy traders will learn to 'ride the
waves' of order flow within markets.
At some level, I expect these concepts to be met with resistance, as traders find
difficulty in leaving 'the old notions' of technical analysis behind.
By this I mean, often when 'the accepted standards' are challenged, some have
trouble letting go of the information that has been taught as reliable for so long, even if
it's flawed. However, reiterating Henrik Ibsen's famous statement from the 1882 play
An Enemy of the People, "the majority is always wrong."
From the shoes of most retail traders, many likely find themselves continually
frustrated from confusing signals from technicals, which often seem completely
misleading in real time. For some strange reason though, many retail traders continue
to believe (or perhaps want to believe) in their 'accepted standard' technicals, despite the
losses surfacing in their accounts.
Really, technical analysis is only true so long as enough people are acting on the
same information at the same time. However, as we saw in Chapter Two, technicals
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are actually failing in today's market, because too many people are acting on the same
'pre-set' information at the same time.
Here's where we start to level the playing field…
We will no longer look at charts as instruments of trading… producing 'signals',
which we trade from.
Instead, we will look beyond the charts.
We will firmly resolve to understand that by looking at charts whatsoever, we are
viewing data and the translation of data and nothing more…
We will also resolve to stop looking at magical technical patterns (hyped,
invalidated signals some schmooze is selling), or bogus Expert Advisors (EAs) that do
not and/or cannot justify their existence from some sort of understandable framework
of descriptive statistics, mathematics, or physics.
In addition, while I've already touched on the aspect of price action as 'data', the
concept must be revisited briefly… just in case.
The 'data' is so much more than just price action, in reality, 'the data' is screaming
aloud…begging us to stop and pay attention for a moment…
The data is saying, "If you take a moment to truly look into me, I provide significant
insights into probability/volatility, order flow and fundamental underpinnings…truly
moving markets."
Fact is, technicals generally only perceive events in the past... Traditional technical
analysis' predictive worth is nothing more than hope that an event that occurred
yesterday, will happen again.
Really, technical analysis is the study of information that has already occurred,
without any regard to the probability of what could truly transpire in the future.
In essence, technical analysis is nothing more than the study repetitive pretty
pictures throughout history.
Unfortunately, there are those who will continue to argue traditional technical
analysis can predict tomorrow… Concerning most signals though, when the technician
is asked 'why will it work again?' most explanations will sound like:
"Because it worked in the past..."
Humbug.
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Technicals work perfectly when studying historical charts; I agree. Nevertheless, the one
time you attempt to trade from one of the supposed super-signals… I can assure you, will be the
one time the signal will fail.
Have you ever entered a trade based on an overbought or
oversold indicator, only to see the trade move against you?
In the amazing book Technical Analysis for the Trading
Professional, author Constance Brown inquires, "How did I
miss such an obvious signal like that one?"
How many traders ever really look into 'why' what is
happening...is actually happening?
Repeatedly, I see traders completely disregard the
philosophical, fundamental, mathematical and common
sense reasoning behind the charts they trade from.
I can assure you that when these traders and investors
grow sick and tired of losing money, they will finally either
quit, or start putting in the time. Regardless, trading purely
off technicals is similar to looking for Braille in the drivethru.
Using our earlier discussion of CCI as an example, when
(for example) the EUR/USD begins ascending and CCI
travels above +100, traders who have based their
understanding of the indicator on 99% of the commonplace
explanations available, one would believe the EUR/USD is
now entering 'overbought' territory.
In reality, the EUR/USD (on whatever timeframe being viewed) is simply moving
outside of (about) the 1st standard deviation mark, which really means 'distribution
potentially on the move.'
The same logic applies to expectant fundamentals, in that enough people have to
believe in a future outcome for the actual trading action to mimic the "perceived
outcome" by those same people.
Even more devastating though, when fundamentals shift, often, many technical
traders are not even aware that the occurrence has taken place and thus, find
themselves not only on the wrong side of the trade, but often stopped out at exact high
and low prints of the relative range too.
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When we begin to understand descriptive statistics not only allow us to intuitively
'feel' the true fundamental sentiment behind the market, while also overstepping the
simple 'hope', which too often comes from traditional charting, we begin to see that
both technical and fundamental perceptions of the larger market are actually
transparent within the data unfolding before our very eyes.
Descriptive statistics are defined as: 43
[1]Descriptive Statistics are used to describe the basic features of the data gathered from an
experimental study in various ways. They provide simple summaries about the sample and
the measures. Together with simple graphics analysis, they form the basis of virtually every
quantitative analysis of data. It is necessary to be familiar with primary methods of
describing data in order to understand phenomena and make intelligent decisions.
Various techniques that are commonly used are classified as:
• Graphical displays of the data in which graphs summarize the data or facilitate
comparisons.
• Tabular description in which tables of numbers summarize the data.
• Summary statistics (single numbers) which summarize the data.
I ask, "How can anyone make an intelligent decision in markets, without understanding the
data at hand?"
See, so many traders use technical analysis to decipher their entry and exits without
truly evaluating the logical validity of the technical signals surfacing.
What's more, tack on complete oversight of the common sense economic
fundamentals and truly, it's no wonder retail traders are often stopped out at the top,
or bottom…or just plain wrong altogether.
The aforementioned aside, let's discuss how technical analysis also completely
overlooks vital "real data" traders need most.
Principally, we know technical analysis is a "lagging event," meaning the action
unfolding on charts can only exist insofar as another event has already occurred.
In short, an equity, index, option, commodity, futures contract, or even currency
must have already witnessed a trade 'print', before the data ever even shows up on a
chart.
Which came first, the chicken, or the egg? In the world of trading, a transaction
MUST always take place before the instance shows up on a chart.
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(To split hairs, one might argue the two events are simultaneous. however, a transaction can
take place without the existence of a price chart, but a chart cannot exist without a transaction,
or series of.)
Really, the true wealth in technical analysis is the identifiable and/or representative
display of empirical data unfolding, otherwise known as descriptive statistics.
When we change the way we think about what we are seeing on charts, we change
our total understanding of technical analysis, especially 'hocus pocus hope indicators'
and/or methodologies built for failure from the start.
When we begin to understand that by viewing and analyzing the data displayed on
charts, from a stance of descriptive statistics, we will begin to see that we can
completely discard the mainstream technical crap foolishly embraced as the 'accepted
standard,' and instead start measuring and utilizing volatility and probability as tools
for profitability.
I hope that readers understand why I'm beating a dead horse… We must
understand that the accepted standards of trading tools presented to the retail
crowd…are flawed.
So how do we overcome the issue through volatility and probability? First, we must
also understand that all data, all price action we empirically see on our charts is:
1. Data coming forward tick by tick.
2. When summed, creates a series of smaller subset distributions, within larger
distributions.
3. No different, or more complex, than any other data measured by statisticians.
How is it we can predict weather patterns, and yet, mainstream media and general
populace investors can't see the Dow tumbling downward through 10,000 one week in
advance?
Anyway, in our discussion of descriptive statistics, we really only going to focus on
the concept of 'normal' (bell shaped) distributions…
The application of normal distributions applies to trading insomuch as the data we
are measuring is constantly moving with the periods we are studying.
What I'm saying is because a subset distribution's mean (seen through a moving
average, for example) is constantly in motion, as prices rise and fall, the 'data' (prices)
will never stay skewed on one side of the mean, or another.
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When studying smaller subset distributions, eventually the data will cross back
over the mean (moving average); because within markets, our means are never totally
stagnate.
The 'traveling factor' behind a moving mean proves that the data we are measuring
will eventually return to the mean, perhaps even crossing above, or below, possibly
even extending significantly in the opposite direction.
It is the concept of the mobile mean (where old data is replaced – i.e. the newest day
of a 50-period Simple Moving Average forcing the 51st day to drop off) that justifies
measuring volatility through standard deviations under the premise of a normal
Gaussian curve. (Really, we're talking about the Central Limit Theorem.)
What's more, as John Bollinger points out in his book Bollinger on Bollinger Bands,
the Central Limit Theorem tells us that even when long-term data is not normally
distributed (as is the case with virtually every financial instrument, including Forex), "a
random sampling will produce a normally distributed subset for which the statistical rules will
hold."44
In short, smaller samples within the market will not produce the kurtosis of the
larger data set.45
Gaussian Curve Revisited
Within descriptive and inferential statistics, we will use a random normal
distribution (Gaussian Curve) to measure volatility via standard deviations. In terms
of the Gaussian Curve, we are looking at a normalized distribution, where the sum of
all values of x, are meant to equal 1.
The previously mentioned means if we are measuring price movement within 21periods on a 5-minute chart (for example), the result should equal a probability of 1.
In other words, the sum of all values that have transpired in the measured period
should present a probability of 1 (an empirical absolute) that the events have
happened. What we're referring to here is a probably of 1 that all of the data presented
will rest within our chart, regardless of where the data is within the chart. As long as
the data exists, we're in business on a probability basis.
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Figure 8.3
Moreover, by using historically measured occurrences of data, we can statistically
infer the probability of future events.
I need to clarify a question a few readers might have lurking in their heads… In my
previous attack on traditional technical analysis, I pointed out that if one were to ask a
technician why most traditional technical signals were valid, he or she, would often be
stuck without a proper response, other than that of the signal having shown to work in
the past.
So why, for heaven's sake, is this statistical junk any better? As I already mentioned,
I'm not going to write a novel showing the mathematical justification for
volatility/probability; however, I believe some explanation is required for peace of
mind.
In statistics, the concept of authenticating data is known as classical test theory,
predictive, or concurrent validity. 46
Concurrent Validity is, "An index of criterion-related validity used to predict performance
in a real-life situation given at about the same time as the test or procedure; the extent to which
the index from one test correlates with that of a nonidentical test or index; e.g., how well a score
on an aptitude test correlates with the score on an intelligence test."47
What we're looking for is the theoretical outcome (on paper) to return a high
correlation value (correlation coefficient) to the real world information presented daily.
How will we do all of this?
As you are likely already aware, data within a Gaussian Curve is measured via
'standard deviations' from the mean.
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The arithmetic mean, of course, is the average of all prices recorded in the period we
are studying. Thus, by being able to calculate the average prices for a particular period,
we can also measure probability of movement away from the mean through standard
deviations (confidence intervals) and thus, the probability of all data truly resting
within our distribution, validating our previous concept that all of our data (in the
timeframe measured) should total 1.
If you remember your old statistics days, you may also recollect that the majority of
all data occurrence probability falls within three standard deviations of either side of
the mean. What we know is that 49.86% of all the data should rest within three
standard deviations of each side of the mean.
In translation, measuring three standard deviations on both sides of the mean,
equates to 99.72% of the data within the period measured.
In other words, there is a 99.72% probability that all of the data will fall within three
standard deviations of the mean.
Breaking the standard deviations down, there is a 34.13% probability our data
should rest on one side (above, or below) of the mean. Moving out a little further, there
is a 47.72% probably that all of the data will sit within two standard deviations of one
side of the mean, and a 49.86% probability that all of the data will rest within three
standard deviations of one side of the mean.
Figure 8.4
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However, while there is one standard deviation to the left of the mean (above a
moving average, in the case of trading charts), there is also one standard deviation to
the right (below), and thus, we know to multiply all of our probabilities by two,
compensating for data on both sides of the mean, not just one.
There is a 68.26% probability all of the data will sit within one standard deviation of
either side of the mean, a 95.44% probability all of the data will rest within two
standard deviations, and a 99.72% probability of all data in our period measured will
reside within three standard deviations of either side of the mean.
In terms of measuring the 'mean' for this chapter, we will only be using Simple
Moving Averages and not Exponential Moving Averages (which put more weight on
near-term price data, over the latter.) It's true Exponential Moving Averages track
price action more closely, however, we're keeping things simple here…
I think John Bollinger presents a great argument for using Simple Moving Averages
in his book Bollinger on Bollinger Bands, asserting that we are simply adding one more
variable to an already complicated scenario, by using Exponential Moving Averages.
I'm not saying that you shouldn't use EMA's, but for these pages (at least for now),
we're going to keep things clean and simple.
As many likely already know, a Simple Moving Average (SMA) is created by
summing the data (close prices, for example) for any given period and then dividing by
the total number of periods aggregated.
For example, on a five-minute chart, a 20-period SMA will present the arithmetic
mean (average) of all closing prices for the past twenty 5-minute bars at the location of
the mean, on the current bar.
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Figure 8.5
The Simple Moving Average, is thus, the 'mobile mean', which we are basing our
standard deviations (confidence intervals) from, attempting to measure total 'probability'
of breadth, or 'wingspan' of the data unfolding on a chart.
As Figure 8.5 shows that we are seeing 'more than just a moving average', rather, we
are seeing a visual representation of the "mean data range" over the past 20-periods,
where we will uncover key statistical data to volatility and probability.
In essence, we are able visually map the middle point of our data curve, by charting
a Simple Moving Average.
With the mean identified, we must now identify benchmarks (confidence intervals),
in an effort to validate our probability distributions, as accurate and usable within
trading. We're really talking about mapping the 'distribution' of data through standard
deviations.
Moreover, we are also mapping the actual distributions to be able to answer the
question of why implementing probability not only accurately reflects the past, but is
also incredibly useful in attempting to perceive the future, over standard technicals.
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In essence, the distribution is really a sort of teeter-totter (unfolding around the
mean), where we are able to actually see how the data is unfolding on our chart.
Figure 8.6
In terms of inferential statistics, we also know there should be a 99.7% probability
that all of the data (in the period measured) will rest within three standard deviations
of the mean…
As the below chart shows, other than two small blips outside of the lower 3rd
standard deviation, almost all (99.7%) of the data does indeed rest within 3-standard
deviations of the mean.
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Figure 8.7
Just incase Figure 8.7 was a little confusing, Figure 8.8 (on the following page)
shows a clearer picture of Gaussian Curve concept on an actual chart.
Please note that I used a 20-period Simple Moving Average (SMA) to measure the
Gaussian Curve in Figure 8.7.
Looking at Figure 8.8, traders will notice that when we simply overlay three
representative curves (denoting the 1st, 2nd an 3rd standard deviations) with the mean
being the 20-SMA, we see how the Gaussian Curve looks when mapping actual data.
Now though, let us think of the Gaussian Curve in another format… Let us imagine
the curve as an actual "teeter-totter" like scale, which will shift higher and lower on the
left and right sides, as the data moves from side to side.
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The question is how we will measure, or map the data shifting from side to side on
the teeter-totter? To provide any insight into ascending, or descending prices, we must
have some way to map distribution data shifting, thus prompting the teeter-totter to
lean in one direction, over the other.
As a solution, we will simply map a shorter-term subset distribution within a
longer-term distribution. As the shorter-term distribution moves from right to left on
the larger teeter-totter, the result should be for the larger teeter-totter to fall to the left,
as the bulk of data begins to add pressure, thus denoting trending…
Think of it like this… Suppose we're standing in a part looking at a big teeter-totter
called the '50-period seesaw', which is for the most part, well balanced. Now imagine I
walk up to it with a box of bricks labeled '20-period stones' and dump the load on the far
left side of the teeter-totter, what would happen to the larger 50-period seesaw?
Figure 8.8
It's a no-brainer of course, the larger teeter-totter would lean to the left…
With a little shameless marketing in mind, I'm going to call the teeter-totter the
Whistler Trending Scale (WTS). Moreover, just to make sure the point of moving
subset distributions is absolutely clear, please again imagine a larger teeter-totter
sitting idle in a park, with both sides suspended in mid-air equally…
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We can generally assume all things are relatively calm (or normal) in that one side is
not dramatically higher, or lower than the other.
However, if I were to set my neighbor's super big chunky ice-cream kid on the left
side of the totter, what would happen?
Everything you own in a box to the left. Now, if you imagine the larger teeter-totter is
50-periods of data, what happens when I slide 20-periods of data to the left?
The key point to note in the WTS, is simply that when the shorter-term data
(measured by a 20-SMA) moves to the left of the 50-SMA (longer-term mean), the scale
should tip down to the left, thus denoting a bull trend.
 Data to the left: bull.
 Data to the right: bear.
 Data significantly flanking either side, but headed back to the center: Mean
reversion.
Figure 8.9
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Historically, the instance of a short-term distribution sliding from one side of the
totter to the other is known as a "moving average crossover". In effect, Moving
Average Convergence Divergence (MACD), comprised of 12 and 26-day moving
averages is an example of a short-term distribution mean sliding back and forth across
a longer-term average.
However, it is important to note that what we are not doing here is simply looking
for instances of a short-term distribution crossing over a longer-term mean for a trade
signal.
Again, what we are not doing in our study of volatility and probability is simply
using mean (moving average) crossovers for signals. Not only would the signal be
lagging, but likely constantly setting us up for failure as our traders were stopped out
on pullbacks surfacing almost immediately after taking a position.
Instead, we will be using distributions (and the outliers of distribution width) to
measure potential future volatility probability and current 'acceleration'
volatility/probability within the short and long-term mass (distributions), we are
measuring.
Moreover, we will use the outliers of distribution width (total mass width), by
means of standard deviations, to identify trend entries and exits for trending and/or
potential consolidation to come.
(Note: The areas shaded more darkly in Figure 8.9 are simply to point out the second and
third standard deviation outliers of the 50-period distribution.)
If you are having trouble with the larger concept of sliding distributions, please take
a look at Figure 8.10, where I have rotated the WTS 90 degrees to the left. The image
again shows how when a shorter-term distribution slides to the left of the mean,
whatever instrument we are measuring…is taking on a 'bullish bias', and vice versa for
distributions sliding to the right. Again, we are not looking for 'moving average
crossovers' here at all, we simply taking note of the occurrence of sliding distributions.
Moreover, instead of eying the precise traveling of the moving averages, our trading
clues will come from the expansion and contraction of the standard deviations framing
the various distributions.
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Figure 8.10
How do we map standard deviations?
As you may have already guessed from Figure
8.7, we can simply apply Bollinger Bands (the
actual application of standard deviations on a
chart); however, we will not be using the typical
settings commonly pre-loaded within charting
packages.
If you are not aware, Bollinger Bands are really
the 'application' of the standard deviation formula
to charting.
I sometimes think many retail traders never
truly understand how powerful Bollinger Bands
really are, simply because the name is slightly
misleading…
Don't get me wrong, John Bollinger is a genius
and one of my greatest market inspirations,
however, what we're really seeing is a probability distribution measured through the
actual expansion and contraction of standard deviations. For the sake of keeping our
terms clear, over the following pages, we will call Bollinger Bands 'volatility bands'.
Again though, I believe Mr. Bollinger is nothing less than a market genius, however,
like so much information surfacing in markets today, many investors are missing the
power of indicator (based on probability theory and statistics), becuase most
explanations of the tool are incredibly misleading.
Here's an example:
One major Website defines Bollinger Bands as:
"A technical analysis technique in which lines are plotted two standard deviations above and
below a moving average, and at the moving average itself. Because standard deviation measures
volatility, these bands will be wider during increased volatility and narrower during decreased
volatility. Some technical analysts consider a market which approaches the upper band to be
overbought, and a market which approaches the lower band to be oversold."48
There we are with our two favorite words again: overbought and oversold.
Whoever wrote the above definition has obviously never traded with real money…
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Foremost, Bollinger Bands (volatility bands) expand and contract because of the
squaring of the deviations in the standard deviation formula, which causes a 'multiplier
effect' in the bands. What's more, even remotely inferring that when price touches the
upper, or lower bands means 'overbought' or 'oversold' is fairly incorrect, at least as
presented to average Joe-Q-investing public. Obviously, a 7-period distribution will
have significantly less mass than a 50-period distribution; thus, usually when price
touches the second standard deviation of a 7-period distribution, price is likely just
starting to near the 1st-standard deviation of a 50-period distribution.
Do you see what I'm saying? The concept of 'overbought' and 'oversold' is relative
to the period measured… I hate to pick on details, but the little snippet of information
the mainstream investment education Website left out…is pretty darn important.
Geesh…
I'm not kidding, this stuff keeps me up at night…
With the previously mentioned in mind, I would like to note that the WTS is
literally a scale of common sense, showing that when we add weight to one side, the
occurrence creates motion whereby the scale shifts. What I'm saying is the tag of the
second standard deviation on a short-term distribution does not mean price is
oversold, the occurrence likely means the lesser distribution (in terms of periods
measured) is shifting on the scale and price is moving…
To clarify the actual movement of a distribution, as seen in price action, in Figure
8.11, you will notice I have drawn a 20-period moving average and a 50-period moving
average, the former with volatility bands at 3.2 standard deviations, and the latter at 1.2
standard deviations. (It is important to note that when drawing volatility bands on
charts, we must always set our standard deviations slightly above where we normally
would, to account for data loss in the electronic application of the formula. By this I
mean, we want to set the 1st-standard deviation at 1.2, the second at 2.2 and so on.)
In terms of the WTS concept, we immediately see the 20-period distribution is now
above the 50-period mean, obviously denoting the teeter-totter has leaned to the left, or
in other words, the EUR/USD is experiencing bullish trading action. There's more to
the story though… Remember the previous discussion of data probability (in relation
to the mean), measured through standard deviations?
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Figure 8.11
Looking at Figure 8.11, we know through probability 99.7% of all our data should
theoretically rest within 3-standard deviations of the mean. In the case of our 20-period
distribution, if a sharp selloff were to occur in the next bar, where do you think the
selling action would likely pause, at least temporarily?
Probability tells us…likely on the lower 3rd-standard deviation of the 20-period
distribution, which is coincidentally sitting almost precisely at the mean of the 50period distribution.
However, as witnessed in the chart, just a short while ago, price actually tagged the
upper 3rd-standard deviation of the shorter-term distribution, before commencing the
present consolidation… The event of price hitting the third standard deviation did not
mean the EUR/USD was oversold, rather, the occurrence just meant fierce buying was
attempting to push the shorter-term distribution into a new range… Now, with the 20period lower third standard deviation still above the 50-period mean, the occurrence of
consolidation could simply be allowing both distributions a moment to 'breathe' and
potentially store energy for another move higher…
The aforementioned is just a quick example of the great power measuring standard
deviations (and the movement of distributions) within markets… You will soon see
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that we can also identify when trending is about to begin, when 'true trending' is in
effect and also when trending has ceased and consolidation is about to commence.
Using concepts of descriptive and inferential statistics, and specifically standard
deviations, we can time our entries to capitalize on volatility induced breakouts and
breakdowns, taking positions when probability of order flow is truly in our favor.
Moreover, we will also know when the probability of continued trending has
ceased, thus telling us to close our directional positions and switch gears to lateral
trading strategies…
It's all probability and volatility, seen through the expansion and compression of
standard deviations and distributions on our charts…
The Expansion and Compression
of Subset Distributions
Jumping right in, Figure 8.12 (below) shows the EUR/USD on a 4-hour chart… We
are again looking at a 50-SMA, with our volatility bands set at 1.2-standard deviations.
We've also included a 20-SMA with volatility bands set at 3.2-standard deviations.
Within the longer-term distribution (the 50-period), we are using utilizing the 1ststandard deviation to derive the smallest portion of probability (in terms of descriptive
statistics), that would infer potential follow through of price away from the mean
(divergence).
We know there is a 68.4% probability that all of the data should rest within 1standard deviation of the mean.
It's also important to note that when measuring 1-standard deviation from the
mean, the occurrence of price moving away from the mean, through the 1st-standard
deviation would line up with 50-period CCI traveling above +100, or below -100.
Again, while the rest of the retail herd is thinking the event is showing the currency as
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'overbought' or 'oversold', because you are more educated and much more savvy now,
you will know that really, the instance just means the distribution is 'on the move.'
Don't you just feel bad for all those other traders attempting to navigate markets
with flawed information.
They've been set up for failure, unlike you…
What the above is telling us is when a currency, stock, or other trading instrument
moves above, or below a longer-term 1st-standard deviation, the instance is NOT
screaming overbought, or oversold, rather, the instance may instead be saying three
things:
1. A fundamental event or coincidental news occurrence has prompted traders to
take action, and is creating a move away from the mean. In essence, there is a
reason the bricks (prices) are sliding to one side of the teeter-totter.
2. If the move is real (not just a 'quick pop' anomaly), the short-term distribution
should 'confirm' the fundamental mindset shift, by sliding over the mean of the
longer-term distribution and then hold reasonable ground during the initial
pullback(s), after the breakout.
3. Short term volatility (measured through standard deviation) will lead price, an
inherent luxury of squaring of the deviations in the standard deviation formula,
when electronically applied to price action on charts. (I will explain this in
greater detail in just a moment.)
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Figure 8.12
If short-term volatility, as denoted by the 20-SMA 3rd-standard deviation spikes
above long-term volatility, as denoted by the 50-SMA 1st-standard deviation, the
breakout is "confirmed."
Why?
What we are seeing is an instance of short-term volatility leading price…
Please allow me a moment to pause and explain a very, very important concept…
If we were simply measuring total distribution mass through probability (standard
deviations), conceptually, we're talking about the total 'wingspan' of the
distribution…or in other words, how 'wide' the distribution is…
If all things were equal, meaning normal and calm in markets…and we were
measuring 50-periods of data and 20-periods of data…and we were measuring total
'width' (mass) of both distributions…and we were doing so by mapping the 3rdstandard deviations of each, would the 20-period 3rd-standard deviations be inside, or
outside of the 3rd-standard deviations, of the 50-period distribution?
Think about it for a moment…
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If all things were equal, meaning prices were in a 'normal state', like not trending, just
calmly traveling sideways, would the total mass (width) of the 20-period distribution
be greater, or lesser than that of the 50-period distribution?
Clearly, the 20-period mass would be lesser (narrower) than the 50-period
distribution.
Why?
We're simply measuring less data. In short, there is greater probability of higher
and lower prices in 50-periods of data, than 20-periods of data, when 'all things are
equal', or prices are in a 'normal state'.
However, when volatility increases, because we're measuring less data in the 20period distribution, the distribution mass would expand quicker than the 50-period
distribution.
The rule holds true when measuring 50-periods at 2.2-standard deviations and 20periods at 3.2 standard deviations as well, though there is slightly more room for trader
error.
Figure 8.13
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Really though, what we're talking about is the empirical state where short-term
distribution width will always expand quicker than longer-term distribution width,
based on the fact that the shorter-term distribution has less mass overall.
Remember our previous discussion of Newtonian Motion and the equation of force?
Force = Mass * Acceleration. The lesser the mass, the greater the possibility of
acceleration and thus, more force to move our distributions. As the Figure 8.13 shows,
when short-term volatility spiked outside of long-term volatility, a significant
downside move in the GBP/USD occurred on the hourly chart.
Figure 8.14 - Repeated
There is even more to the story here though…
Back on our original chart of the EUR/USD (Figure 8.14), readers will notice when
the EUR/USD touched the topside 3rd-standard deviation of the 20-SMA, the pair
quickly fell back to the 50-SMA mean, before resuming the ascending trend.
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The longer the period measured, the greater the probability prices will fail at the
3rd-standard deviation. What's more, in shorter-term periods, prices tagging the 3rdstandard deviation denotes three events occurring:
1. Short-term volatility has accelerated to a point where prices are tagging statistical
'outlier' variables.
2. Trending will likely ensue.
3. Before trending ensues, a pullback to the mean, or 1st standard deviation is
highly probable.
See, we know statistically, there is a 99.7% probability that all of the data will sit
within 3-standard deviations of the mean. Thus, on a short-term basis, if we have
bought a currency pair in a bull-trend and the pair strikes the shorter-term 3rd
standard deviation (on the topside volatility band), we may want to consider taking
profits.
It is important to note that price touching the 3rd-standard deviation does not mean
the trend is over, rather, simply that a pullback to the mean may perhaps, be in the
cards… Then, we can attempt to re-buy the pair on the mean, if we believe the trend is
still intact.
Moreover, if price has just hit the third standard deviation and short-term volatility
is collapsing back below long-term volatility, we can rest assured price is indeed about
to consolidate, or reverse. Why? Simply put, price cannot move up, or down if shortterm volatility is compressing. Because of the squaring of the deviations in the
standard deviation formula, the application of standard deviations to price data creates
a 'multiplier effect' in the lines representing the standard deviations.
What I have just mentioned is the reason volatility bands expand and contract,
providing us with key information regarding the release of energy within price action
and thus, the expansion and compression of distributions.
It doesn't matter if you're looking at a 5-minute chart or a weekly chart, if short-term
volatility is expanding, prices are trending in the period measured. Moreover, if shortterm volatility is compressing, prices are consolidating.
Figure 8.15 shows precisely what I'm talking about…
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As you can see, when short-term volatility (measured through the 20-period 3.2
standard deviation) compresses, in every occurrence, prices travel laterally until shortterm volatility begins expanding again.
Moreover, as you will also notice, both times when short-term topside volatility
attacked long-term volatility and compressed back below, the occurrences were almost
precisely where the EUR/USD stalled on the upside.
Why?
Again, price simply cannot continue trending if short-term volatility is compressing.
Short-term distribution width (mass) as measured through the 3.2-standard deviation,
otherwise known as topside volatility, must be traveling upward for bullish action to
continue.
Why?
If short-term volatility is compressing, the occurrence means the distribution is
'compressing' and a distribution must release energy to move, not vice versa. Shortterm distribution width (mass) as measured through the 3.2 standard deviation,
otherwise known as volatility, must be expanding for directional action to continue.
See, price movement in markets is about order flow, which is really about the
expansion and compression of energy in subset distributions. Logically, short-term
distributions must release energy first, thus stimulating the same occurrence in longerterm distributions.
You will read more about the 'release of energy' in the following chapters so if
you're having trouble fully comprehending, or believing, this 'energy expansion and
compression' thing, don't worry…
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Figure 8.15
You will see the exact same occurrence in Figure 8.16, with short-term volatility
expanding outside of long-term volatility on the downside, prior to the EUR/USD
plummeting on the 4-hour chart.
As short-term volatility remains outside of long-term volatility, trending continues.
Then, just like clockwork, when short-term volatility compresses back below long-term
volatility, the move is over and lateral trading ensues.
One more time, when short-term volatility is outside of long-term volatility, we will
likely want to use trending strategies. Conversely, when short-term volatility collapses
below long-term volatility, we will likely want to start using short-term term channel
trading strategies, while continually eyeing a possible longer-term "trade with the trend"
entry.
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Figure 8.16
If we were able to close a position when short-term volatility collapses below longterm volatility and then open the position back up when short-term volatility begins to
expand, we are (in essence) putting significant probability in our favor, to ride a larger
wave of market action, otherwise known as energy expansion, or trending.
Of note, when traders begin to apply all of the aforementioned to their own charts,
there will be instances of short-term volatility expanding (with price moving),
however, just at the time short-term volatility actually moves outside of longer-term
volatility, the price reverses. Why? Because the longer-term distribution had too much
mass to start with.
Please remember: Force = Mass * Acceleration.
It doesn't matter how hard you try… You (the person reading this book right now)
cannot push a dump truck full of lead up a mountain. The dump truck has too much
mass. So how do we measure mass in terms of trading and price distributions?
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We can measure mass two ways:
1. Visually, you can look at the total width of the longer-term distribution and
gauge (with common sense) whether the distribution is too wide to begin (or
continue) trending, or…
2. You can use the indicator I have developed and supplied with this book titled:
Whistler Active Volatility Energy • Price Mass (WAVE • PM). I will explain
WAVE • PM in Chapter Twelve.
For now, another problem likely persists for traders… How to denote trending?
In the Figure 8.17, I have inserted a 50-SMA 1.2-STD, a 50-SMA 3.2-STD, and a 20period 3.2-STD, while also adding two 3-period SMA's (the darker two black lines
closely tracking price), one measuring highs and one measuring lows.
Working from left to right in Figure 8.17, we see trending was confirmed when
short-term volatility spiked outside of long-term volatility, as denoted with the 20-SMA
3.2-STD spiking outside of the 50-SMA 3.2-STD. What's more, the EUR/USD also fell
below the 50-period 1.2-standard deviation, indicating the larger distribution was on
the move. The instance of the EUR/USD falling below the 50-period 1.2-standard
deviation would have shown up on most CCI windows with the 50-period CCI falling
below -100, which clearly did not mean 'oversold', rather, the occurrence was shouting
'distribution on the move'.
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Figure 8.17
As the chart shows, the downside move stalled when the 20-SMA 3.2-STD collapsed
back below the 50-SMA 3.2-STD.
For those who were thinking there was more downside to come (at least
immediately, anyway), volatility/probability traders knew the move was over and
mean-regression (at the very least) was in effect.
What I've just mentioned was clearly noted not only when short-term volatility
collapsed back below long-term volatility, but also when the 3-SMA lows crossed back
over the 50-SMA 1.2 STD, implying downside order flow was no longer in effect and
shorts would be squeezed.
Using short-term highs and lows of the 3-SMA (traders who prefer a little more
'wiggle room' can use 10-period SMA's off highs and lows) we are able to quickly
identify when the highs and lows of the immediate range fail support and resistance.
What's more, because we are measuring 3-periods of data, it will take more than one
freak candle of upside, or downside volatility to truly change our directional bias.
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By using the 3-SMA for confirmation, we are able to further isolate head-fake
moves, from true trending.
You will notice that while the EUR/USD was channeling, both the 3-SMA highs and
lows never moved above, or below the 50-SMA 1.2-STD. Again though, the actual
instance of trending was not confirmed until short-term volatility spiked outside of
long-term volatility.
What's more, as the chart shows, the WTS would have moved violently to the right,
thus inferring trending to come, as the short-term (20-period) distribution moved to the
right side of the long-term (50-period) teeter-totter.
Shown in Figure 8.17, recognizing volatility spikes can yield big moves, as noted in
the almost 300-PIP drop in the EUR/USD.
It's important to note that in the framework of the information here (as always)
common sense is required.
As you may have noticed, in the above chart, short-term volatility did not constantly
stay outside of long-term volatility…
The instances of short-term volatility compressing are marked with price moving
back to the 20-SMA, but did not fully reverse. Every extended move in markets will
see pullbacks as volatility reloads for another move…
In the above chart, we also know the EUR/USD never violated descending
resistance of the relative range, until the trend completed itself. Using the 3-SMA
(lows); however, would have absolutely closed the trade before descending resistance
was violated, thus perhaps saving a few PIPs of profit.
What's more, in one instance (a little over halfway through the move) the EUR/USD
struck the 3rd-standard deviation of the 20-period distribution. Savvy traders may
have inferred it was time to take profits; thus setting themselves to re-enter -with the
trend, at the 20-SMA mean (which was precisely at descending resistance as well.)
In addition, as previously noted, because the 3-SMA lows never moved above the
1.2-standard deviation of the 50-period distribution, taking a long-position any time
during the decline would have been foolish.
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Figure 8.17
Regardless, it is important to note that when trending ensues, we should always
attempt to understand why the move is occurring in the first place, on a fundamental
basis. However, with a little common sense understanding of descriptive and
inferential statistics, distributions and probability, all of the information here should
help traders identify trending, channeling and reversals.
Again though, common sense is king, and if you're not sure why what's happening
is happening…as a rule of thumb, "when in doubt, get out."
We have just covered volatility and probability (in terms of mobile subset
distributions), based on 'price action' alone.
It's important to note what we did not cover is volume/dollar volatility/probability
as well. Price action is reliable when we understand that it is…
…purely price action.
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Looking towards volume/dollar trading action as well, we will now jump into
Chapter Nine, were we will discuss VWAP (Volume Weighted Average Price), thus
adding another variable for aggressive intraday traders seeking to capitalize on
volatility…
After our introduction of VWAP, we will enter into a more detailed discussion of
'institutional order flow' and then tie everything together through Whistle Active
Energy Volatility • Price Mass (WAVE • PM).
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CHAPTER NINE
Volume Weighted Average Price
(VWAP)
In currency trading, many retail traders can lose fortunes, before ever even hearing
about VWAP. It's an odd occurrence really, that so many self proclaimed 'high-tech' at
home traders navigate markets daily without even having the faintest clue about
institutional trading performance benchmarks, like the one I have just mentioned.
Clearly, the simple fact that so many retail traders have no clue about VWAP simply
proves success continues to rest within the hands of those controlling the bulk of order
flow.
VWAP (Volume Weighted Average Price) is really a moving average of price,
weighted for the amount of shares that are traded over the duration of the period
measured.
For institutional traders running order flow, VWAP is used as a major benchmark of
performance for those seeking passivity in order execution. In other words, trading to
VWAP is a type of dollar cost averaging during the session, as measured by the
volume/dollar average of the session, or whatever period measured.
VWAP is calculated using the following formula:
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Where:
PVWAP = Volume Weighted Average Price
Pj = price of trade j
Qj = quantity of trade j
j = each individual trade that takes place over the defined period, excluding cross
trades and basket cross trades.
In terms of execution, there are two type methods, which most institutions use:
1. Guaranteed Execution
2. Target Execution
Guaranteed Execution is where a broker explicitly 'guarantees VWAP, or better' for
clients, meaning the broker guarantees the VWAP price, or better, or usually, the trade
is free. What this means is that in a rapidly ascending market, the broker's computer(s)
will likely buy boldly on dips, to ensure the 'guarantee' of VWAP, or better holds, as
prices rise into the day.
Target Execution is usually a less expensive commission process for clients, as
unlike guaranteed execution, target leaves more discretion to traders, while also
requiring more price dispersion…
What this means is there is usually greater 'spread' in total execution price, in
relation to VWAP.
Let's break VWAP down to more simple terms… VWAP is the total dollar average
of the shares traded in a day, or in a given period…
VWAP differs from a basic moving average in that the calculation takes into account
the dollar volume of the instrument (measured through volume) traded in any given
time period. Conversely, moving averages simply calculate the 'average price' over a
given time period, without recognition of volume.
Don't worry if the aforementioned sounds a little foreign, or confusing right now; it
may take a little while for the concept to sink in. (Especially why keeping an eye on
VWAP is so important!)
In reality, VWAP is a definitely a 'paradigm shift' for most retail traders…
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Why?
Retail traders seek to make money when a stock, currency, commodities, or futures
price moves up or down. In essence, the retail trader has been conditioned to believe
his sole 'opinion' about price action in markets, should be to know whether prices are
moving up, or down. Retail traders believe the better the trader you are, the more you
will know whether prices are about to ascend, or descend. Little does the retail trader
know, intraday action is more about risk and fill, over the up, or down 'opinion' of
prices.
For the institutional traders attempting to 'work orderflow' he or she knows trading is
really about risk, in relation to benchmark performance.
At the end of the day, institutional traders simply seek to achieve the best
possible prices possible for their clients.
In terms of institutional trading, large orders are broken down into smaller orders,
which are then 'worked' (via trader, or computer, or both) over a given period.
The phenomenon of breaking large orders into small orders and then working the
little orders over a period of time is called 'iceberging' and is intended to lower the
overall cost of the transaction, while keeping the large order out of the sight of other
market participants.
Please take a moment to observe the below table… In column two 'Price' we can see
over a given period (it could be 1-minute, 5-minutes, 1-day, whatever…) there were
two transactions: One buy at $24.50 and one sell at $24.00.
Figure 9.2
Volume
Bought
Sold
Volume
Moving Avg
Bought
Sold
Volume
Price
1000000
500000
1500000
$24.25
300000
200000
500000
2000000
Moving Avg $22.90
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Total
$24.50
$24.00
$48.50
$24.33
$23.30
$22.50
$45.80
$94.30
$24.00
•
24500000
12000000
36500000
 VWAP
6990000
4500000
11490000
47990000
 VWAP
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If we were using a simple moving average, the actual line on the chart would be
marked at $24.25, which is the average of the two prices.
However, if we were to incorporate the volume traded in the same period, the
moving average line would instead be marked at $24.33.
Why?
As the below image shows, when we calculate VWAP, we are actually multiplying
volume by price, summing the calculation and then dividing by the total volume in the
given period…
For our price of $24.33, the math would be:
[(1,000,000 * $24.50) + (500,000 * $24.00)] = 24,500,00
Then we would divide 24,500,000 by 15,000,000 (the total volume traded in the
period) to get the VWAP of $24.33.
What's so important to understand is that while a simple moving average provides
the average (middle, mean, or mid) price of the period measured, VWAP actually takes
into account the fact that more shares were traded at the higher price, versus the lower,
thus giving us a more accurate indication of whether there are more buyers, or sellers
in any given period.
Figure 9.3
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Do you see the implications here?
A simple moving average is nothing more than present a line with a 50/50 guess of
whether buyers or sellers were present. However, VWAP actually provides greater
insight into the actual buying and selling that occurred in any given period.
Can you see why price action technical analysis can often set retail traders up for
failure from the start?
The aforementioned does not mean we can't use moving averages, or price action
only technicals, we simply must understand moving averages and other technicals do
not take volume into account.
We must understand that price action is a derivative of volume and that without
volume (the actual instance of a transaction), price cannot exist.
Again, price action moving averages are not totally misleading… After all, we are
measuring the average of prices (and nothing more), over a given period.
Used in conjunction with VWAP (in terms of volatility/probability, as mentioned in
the previous chapter), moving averages are a great identifier of 'average distribution'
price movement.
In terms of VWAP, here's what readers must understand…
What we're talking about is a benchmark of price, which institutional traders are
measured by, in terms of commission structure and performance.
If you're an institutional trader and you receive a buy order for $40 billion
EUR/USD, your client needs some sort of way to measure whether you've done a good
job of filling his order in relation to the prices of the day… Thus, if you receive a $40
billion order for whatever, chance are, you're not going to be able to fill the whole order
in one shot, without creating a stampede. Thus, you need to fill the order slowly over
time, whereby your client will then measure your overall performance with some sort
of benchmark of average prices throughout the session.
Benchmarks include VWAP, TWAP (Time Weighted Average Price), LHOC (Low,
High, Open, Close [average]), just to name a few.
The bottom line is, if you are an institutional trader and you are able to consistently
fill your clients orders at prices better than VWAP (or other benchmarks), everyone will
likely be very happy. What's more, in some cases, traders are even paid bonuses for
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achieving better fills over time. While there are many benchmarks institutional traders
are gauged by, the most widely coveted is VWAP…
With this in mind, please look at the following two charts, Figures 9.4 and 9.5.
In Figure 9.4, we are seeing 14-period, 21-period and a 50-period regular Simple
Moving Averages. What I would like you to immediately take notice of is the fact that
if we were looking at shorter-term moving averages, like the 14-period and the 21period, the (on the 5-minute chart) the EUR/USD pierced the moving averages three
times, once in the beginning of the rally and then twice towards the end. For the at
home trader, this price action likely just looks like "volatility."
Figure 9.4
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Figure 9.5
Now, if we look at the Figure 9.5, however, we see that the EUR/USD attacked
5,000-tick VWAP twice, which it stalled at almost precisely…
In Figure 9.4, the 50-period SMA is the only technical moving average that comes
close, but still, the EUR/USD did not actually 'touch' the indicator.
So what's happening here?
Foremost, we must remember that price action only moving averages are nothing
more than technical indicators of 'average price'.
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It's important that you understand this concept. Moving averages, at least in-terms
of providing accurate trading signals, are nothing more than indicators that only hold
if enough people act on the same information at the same time.
VWAP is similar, except that the 'people' acting on the information are institutional
traders, who control the bulk of the order flow. Do you see how important this
paradigm shift for retail traders is?
If you want to know where order flow is, than it's important to watch an indicator
that shows what and where institutional traders are looking at… Not just a simple
technical tool that is only relevant from time to time, most often by luck and luck
alone…
If we want to use moving averages, than we need to understand that they should be
used as, 'benchmarks for volatility distributions' and not fancy technical analysis trading
signals, with no real explanation…
Figure 9.6
When distributions move
above and below one another
(like a 14-period moving average
crossing under a 21-period
moving average, for example) we
should be thinking: On a price
action basis alone, the shorter-term
volatility distribution just moved
under the longer-term
distribution…
What we should not be
thinking is: The red line crossed
under the blue line and that's a
definite sell signal.
Now, if we take a look at the
next chart, you will notice I have
drawn two more lines, a 34period Simple Moving Average
and 10,000 tick VWAP.
It is important to note that I
added the 34-period only after
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'trying' to make several moving averages fit VWAP.
In the case of the 15-minute chart, the 34-period was the closest benchmark moving
average I could find.
Unlike the 34-SMA, the 10,000 tick VWAP is a constant value that traders can use (at
least for the time being…remembering that everything eventually changes within
markets) when attempting to wiggle into the mindset of institutional traders.
What is so important to understand here (reiterated again) is the 34-period is
nothing more than a technical indicator of average distribution price action.
However, VWAP is an actual institutional benchmark that many of those who are
working BIG orders, are likely watching to time their trades.
Figure 9.7
If you had $40 billion in
orders to work, would you buy
as close to VWAP as possible, or
way above it, like many at-home
technical breakout traders?
Of course you would buy into
VWAP, knowing that if the
EUR/USD were to then begin
rallying again, your buy would
be under VWAP, as VWAP
continued to ascend.
Again, In the shoes of the
institutional trader, he would
want to buy a pullback into
VWAP, if the trend looked like it
was going to stay intact,
knowing that another leg up
would move VWAP higher, and
thus, provide the trader a better
fill than VWAP for the day.
If the EUR/USD were to
break below VWAP, the trader
would likely sell inventory,
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knowing he would likely be able to buy lower, as selling tapered later on.
The 34-period held as a buy signal (with the trend) in the first leg of the up move,
but VWAP was more accurate in the final instance of 'test' before the last wave up.
Why?
Foremost, because if a trend is truly to stay intact, institutional traders will buy into
VWAP, attempting to time their trades as close to the benchmark as possible. Institutional
traders don't look at other technicals like MACD, or goofy awkward period moving averages.
Unfortunately, because the at-home trader hardly has any real information, and was
likely inferring a sell signal when his 14-period and 21-period moving averages were
breached, or other momentum indicators were showing signs of being overbought, the
retail trader likely got short, while the institutional trader was buying exactly into
VWAP…
As the Figure 9.7 shows, three times during the uptrend, retail traders were given
sell signals by stochastics (using the common preset variables of 5,3,3).
Do you get it?
Do you see it?
Please tell me you see how conventional indicators completely set retail traders up
for failure!
I'm not joking about this stuff…
Most of the technical indicators retail traders look at are nothing more than pretty
lines on a chart…
Retail traders who were watching the 15-minute chart and stochastics (Figure 9.7),
were likely scratching their heads saying 'geez Forex is volatile'; however, the savvy
trader who understands VWAP and volatility/probability knows there's more to the
picture… Savvy traders know trading profitably is more about the minds of those
working institutional order flow than a few dim-witted lines on a chart.
This is Volatility Illuminated .
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Figure 9.8
Okay…I hope you're asking if there's a downside to VWAP?
If you are, you get a gold star.
Just like any indicator, VWAP will not illuminate everything that is happening
within the market, all the time.
When a currency crosses over VWAP, the occurrence does NOT always mean a
reversal is pending…
In fact, Forex markets sometimes move all over VWAP, providing virtually no
insight into the institutional mindset.
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If you look at Figure 9.8, you will notice that when the ascending trend ended (or at
least, slowed), the EUR/USD traded all over the place (above and below) both VWAP
and the 34-period moving average. The at-home trader was likely taking some
serious licks during this time… And the institutional trader may have been too.
The aforementioned is why I am coming forward with WVAV and WAVE • PM
which will help both institutional and retail traders solve some of the problems
mentioned above.
(Please note that the WVAV strategy was built for institutional trading. In fact, WVAV
could very well even save institutional traders working billions in order flow, piles of
commission cash, by knowing when lateral markets are about to ensue, and when trending is
truly in effect.)
As we move forward into our discussion on WVAV, we need to remember:
VWAP is a glimpse into what the institutional trader is thinking in identifiable
situations of trending.
VWAP by itself isn't enough.
However, when we add VWAP together with volatility bands (WVAV) and WAVE
• PM (price distribution mass) we will have an edge many traders never do.
The true gem behind WVAV is the indicator is almost a sort of artificial intelligence
in and of itself, as the methodology provides guidance into when markets are about to
(and will continue to) move sideways, and when volatility is foreshadowing and/or
sustained trending.
In effect, with what I'm about to show, traders will know when to use lateral
'channel trading' techniques and when to buy pullbacks, with the trend.
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CHAPTER TEN
- WVAV WHISTLER VOLUME
ADJUSTED VOLATILITY
We're finally here… The explanation of WVAV. Before I jump in, I would like to
provide readers with a little background of some of the events over the past year,
which helped bring WVAV to life.
In the fall of 2008, I traveled all the way to Dalian, China to speak at the amazing
Global Chinese Financial Forum, hosted by ChinaWorldNet.com.
I then journeyed to Guangzhou, China (75 miles outside of Hong Kong) to work
with traders and programmers from ECTrader.net, to breathe life into the concepts at
hand.
I would also like to mention the WVAV (as you are about to read about here) is not
a 'cut and dry red line crosses blue line signal system.'
Instead, WVAV is part of a larger methodology, helping to derive trending and
consolidation, while also providing some insight into potential institutional mindset.
Furthermore, using the information in the following pages will require some common
sense. If you're looking for a 'red line crosses blue line' signal, this is not it. However,
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with some rational analysis of the situation at hand, I think you will find WVAV an
extremely powerful tool like no other (readily available) without spending thousands
of dollars.
We will now begin our discussion of what WVAV is and how the indicator assists in
understanding order flow and institutional motivations, and why such is both
important and valid.
What is WVAV?
WVAV is really three pieces combined to sum the whole. WVAV consists of:
 Two indicators of VWAP in the same period, but measuring different data.
 Two sets of VWAP volatility bands.
 Two normalized measurements of price distribution 'energy', otherwise known as
'mass', also known as WAVE • PM.
In the end, over ten years of research went into the 'theoretical makeup' behind
WVAV and WAVE • PM.
Really, the philosophy and theory behind WVAV and WAVE • PM are why the
indicators are novel within today's 'light speed information' markets.
In essence, we are approaching markets from a stance of physics, while also
incorporating volatility and probability within the movement of distributions…
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Measuring Mass and Energy
There are a few simple guidelines of theory readers must understand about WVAV
and WAVE • PM …
Foremost, we are talking about the movement of mass and the energy required to
move whatever mass we are measuring. Understanding the concepts here, we will
need to put effort into reshaping the way we think about price movements in
markets…
Movements in markets are not purely about directional price action…
Movement in markets is about the expansion and compression of energy.
As an analogy, please think about markets as a big rubber ball… When all things
are neutral, the ball is round and centered… However, because money is involved,
markets (currencies, equities, options, commodities, futures, whatever…) NEVER stay
completely neutral, or round.
Why?
Again, because money is involved.
Individual speculators, corporations, funds, Governments, brokerages and a variety
of other players are constantly trying to make money on movements within markets...
Figure 10.1
Movement is based on the perceived value of
the financial instrument today and the expected
value of tomorrow.
Thus, because the news of today is always
shadowed by the unknown of tomorrow,
participants are constantly buying and selling
positions in an effort to profit from the expected
movement of any moment beyond now.
The aforementioned is partially why regular
technical indicators fail… Typical technicals
only present data that has already occurred,
without guidance into tomorrow, other than
some type of expected (reoccurring) similarity
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to what happened yesterday.
However, tomorrow is never exactly like yesterday or even today, which is why
technical indicators constantly seem to provide false signals, with every new day that
passes.
What's more, it's important to understand one more very important concept…
Really, in terms of volume, we have again arrived at the chicken before the egg, or
the egg before the chicken argument.
Does price action appear before volume, or does volume appear before price action?
The answer is volume precedes price.
One must first effect a transaction (meaning a certain dollar amount must not only
be tendered to buy, or sell, but accepted, as well), before a price can print on a chart.
What this means is all technical analysis is a derivative of price action, which is a
derivative of volume.
Thus, we can use price action in determining volatility and probability (and/or
other indictors) only so long as we understand the reality of the situation unfolding.
When we use technicals based off price action alone, without direct reference to
volume (dollars put into action) in markets, we are missing the 'origination' of the
larger picture: volume.
Do we drive without a gas gauge? No way.
We have to know how much fuel is in the tank, before embarking on a trip. If we
have no idea what's going into the engine (or how much is in the tank at all); how far
will we make it?
No very far at all.
Volume buying, or selling at any given level is our gas gauge. If price is moving up
and hardly any buying volume occurs, the gas going into the engine is weak, and will
likely cause a sputtering breakdown.
What's more, without a 'gauge' of the 'effectiveness' of the gas and/or a gauge of how
much gas is in the tank, we are trading two-fold blind.
Thus, technicals (that do not take volume into account) are a measurement of output
and not the 'fuel' going into the engine. Anyone can look back and measure total miles
traveled in a trip, but it takes a more savvy driver to calculate how many miles are
feasible, based on the gas in the tank, and the quality and impact of, in terms of miles
per gallon, as we look towards a trip ahead.
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Traders who solely use 'price action derivative indicators' are attempting to use
historical trips, as a measurement of future possible miles. The problem is that the
upcoming trip very likely has much different terrain, than the previous drive.
Here's what I mean:
Did you know that driving at an elevation above 10,000 feet can cause your car's
engine to have 34% less power output, "due to a combination of lowered oxygen levels, and a
significant reduction in atmospheric pressure."49
Metaphorically, when a stock, currency, or other financial instrument rallies heavily
at 'high altitude', the event likely infers traders 'stepping on the gas', given the emotion
and intensity of the situation. However, just like automobiles at high altitude, more
gas is required to compensate for the loss of power…
Traders 'step on it' causing a fierce rally (like the steep 5th wave upward in Elliot
Theory.) However, the higher the altitude, the greater the likelihood of the engine
breaking down and possibly running out of gas too, based on the lead-foot
overcompensation taking place.
While the aforementioned might seem like overkill, the point is we must know
what's going into the engine and how the fuel is not only affecting, but interacting with
the motor, if we expect to truly see high-performance.
Utilizing volume within trading is 'foresight', using 'price action' technicals alone, is
hindsight.
Back to the round ball explanation…
The ball is basically a distribution of market action showing trending, or
consolidation. What's more, because information is moving at the speed of light today,
markets hardly ever stand still.
Thus, we need to understand the theory behind 'compression' (consolidation) and
'expansion' (trending) of the energy moving distributions within markets.
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Figure 10.2
Now, please look at Figure 10.2. What's
happening to our ball?
You guessed it… The 'ball' compressed! Well,
maybe you didn't guess it, I really don't know.
The point is that when pressure is applied
to the ball, we see 'compression', or lateral
trading.
Also, please note that the compression is
being caused by 'Big Fund Bob' sitting on the
market (please don't laugh at my artwork again!)
Here's where some understanding of
volume really comes into play, for the retail trader. See, most at-home traders believe
that volume is required for a 'surge', but really…this is not always the case.
Often, the volume is really from 'Big Fund Bob' sitting on the market, because he
can't make up his mind. When markets travel sideways, we are really seeing big
players slugging out order flow, without guidance to future direction. In essence, the
large players are lacking insight, just like the little guy. During this time of 'lateral
trading', 'consolidation', or 'storing of energy', markets travel sideways, while
participants struggle to find information to motivate a larger move up, or down. I
know this is contrary to what most retail traders believe, thus, please take a moment to
look over the below chart…
In following hourly chart of the EUR/USD (Figure 10.3), readers will notice the
currency pair witnessed a fierce upward rally on March 18th and 19th of 2009.
The rally really only lasted a little over a day...
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Figure 10.3
However, the following seven days (the 26th and 27th are not visible) witnessed
lateral trading.
What's more, during the 20th to the 27th, the EUR/USD experienced seven (three
visible) volume surges before taking out support in the 1.3418 area.
See, what we have to understand is volume
isn't always the sole motivator of rallies and/or
breakdowns; rather 'volume' can be Big Fund Bob
sitting on a currency, stock (or whatever), both
ways.
Big Fund Bob isn't sure what the outcome is
going to be either, and so a sort of trading tug-ofwar takes place, while bigger players 'jockey for
position.'
What's more, in sideways markets, volatility
and hedge players step in to take advantage of
the situation too.
Figure 10.4
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Fact is, energy is stored in markets (seen through volume and compression of price
distributions) when Big Fund Bob is sitting on the ball, meaning the larger players are
stifling directional movement, fueling lateral trading action.
Without clear news, or information that presents greater and more transparent
expectations of tomorrow, than today; markets will travel sideways, thus 'storing
energy'.
So what happens when Big Fund Bob 'gets off' the bid and/or ask? An explosion of
movement occurs…
In the case of the EUR/USD, the lateral trading action was partially motivated from
Big Fund Bob keeping the pair from traveling higher.
What's more, when the EUR/USD took out support, other funds, institutions and
retail traders were prompted to dump positions, hence the extended 'pullback.'
Figure 10.5
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Another point to quickly mention, as Figure 10.5 shows, the pullback pierced the
61.8% Retracement slightly, before attempting to resume an ascending move… Retail
traders who took long positions right on the key Retracement were likely stopped out
in the 'volatility pop', only to watch the EUR/USD reverse and move higher later on.
Over the past year, I've been receiving increasing amounts of email from retail
traders complaining of excess volatility and indicator failure… This example should
again serve as proof of the pudding that 'excess volatility' (in terms of common
indicators failing slightly and/or entirely) is readily present in today's market. Because
we now have an entire army of retail traders who are acting on the same information,
at the same time, with the same pre-set technical indicator inputs, short-term 'quick
pop' volatility is increasing.
When the technicals fail, like a herd of lemmings, the retail traders rush to cover, or
are electronically stopped out, causing an excess 'pop.' Retail volume is not enough to
keep a trend intact, which is why the 'pops' usually occur at key technical levels and
then reverse.
Overall the critical concepts to understand here are:
1. Market movements are about the expansion and compression of distributions.
2. Volume doesn't always have to persist for a torrid trend to ensue. Often,
heavy volume causes sideways trading, a point many retail traders are
unaware of.
3. The longer an instrument compresses (stores energy) the greater the
likelihood the expansion period will be fierce.
4. Stock technical indicators rely on price action alone and are devoid of critical
dollar/volume data needed to trade successfully on a short-term basis. We
can (and will) use technical indicators that rely on price action alone, but we
must understand that the indicator relies on price action alone.
5. If we can map the expansion and compression of energy within markets, we
really are measuring the probability of volatility (measured in total width of
distribution) where big money will step up, or fade.
6. The physics mumbo jumbo I discussed in Chapter Seven is extremely
important as market movements (seen through volume/dollar/price action,
derived from the expectations of market participants) are about order flow,
seen through energy and mass, not technical analysis.
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Additional NOTE:
Before moving forward, I would like to take a moment to reiterate a few facts again
from Chapter Two - Why Indicators are Failing in the Current Market.
According to the Bank for International Settlements' Triennial Central Bank Survey
(Foreign exchange and derivatives market activity in 2007), Bank for International
Settlements' Triennial Central Bank Survey (Foreign exchange and derivatives market
activity in 2007), "the median share of electronic execution is 17% for non-financial
customers."50 The point here is retail traders do not move markets over the long haul.
However, according to the Wall Street Journal, "Volumes on dbFX, the online retail
trading platform from Deutsche Bank, increased 37% in the first quarter of 2009, from
the same period a year earlier."51
More retail traders have entered the game.
What we're talking about is a fresh wave of neo-volatility from a whole new set of
traders (now at the table) who might not really know what they're doing.
New traders use preloaded technical analysis variables, which as I've mentioned,
increases the 'mass army' of at-home traders doing the same thing at the same time, on
information that really isn't that great in the first place.
What I'm saying is: expect even more 'quick pop' volatility, directly at key price
action technical levels, in the weeks, months, and years to come.
The problem is only going to get worse…
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Mass and Energy through
Standard Deviations
Coming back to our discussion from Chapter Eight, we can measure energy through
volatility, also known as the total width of distributions, a critical component of mass.
When a distribution is wide (meaning a ton of mass) the more volume (buying or
selling) required to continue the trend (or distribution expansion.)
The more mass an object has, the more energy required to move it.
We will now move directly into our discussion of Whistler Volume Adjusted
Volatility (WVAV), in terms of volatility/energy. Then, in Chapter Twelve, we will
cover Whistler Active Volatility Energy • Price Mass (WAVE • PM).
The overall concept, as you're about to see, is fairly simple… Again, the theoretical
underpinning was the difficult part to unearth; the coding (with ECTrader.net in
China) was less of a struggle, once the ball was rolling.
At the core of WVAV, we are using Bollinger Bands (volatility bands) to measure
price trending, and/or consolidation.
By the way, I would like to again reiterate that I believe Bollinger's application of
standard deviations to price action, was perhaps one of the greatest trading
breakthroughs, seen in modern times.
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Figure 10.6
So how does volatility come into play with WVAV and Bollinger Bands (volatility
bands)?
As previously mentioned, volatility bands are a measurement of total potential
distribution wingspan (mass), through the total potential 'width' the standard
deviations are displaying on our charts. As mentioned in Chapter Eight, when we map
a distribution, we seek to measure probability from the mean, by one, two and three
standard deviations.
Figure 10.6 again shows, there is a 68.3% probability that all of the data will fall
within 1-standard deviation of the mean, a 95.4% probability all of the data will rest
within 2-standard deviations and a 99.7% probability all of the data will be parked
within 3-standard deviations of the mean.
(Please note again that actual Bollinger Band settings need to be 1.2, 2.2, or 3.2 standard
deviations and not whole numbers, accounting for data loss in the conversion of standard
deviation formula – into electronic format on charts.)
Again, the brilliance of Bollinger Bands (volatility bands), is simply the incredible
fact that the squaring of the deviations in the standard deviation formula (when your
computer calculates the bands) creates a type of 'multiplier effect', causing the bands to
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expand and contract with volatility. When prices consolidate the bands compress and
when prices trend, the bands expand.
While this may sound lowbrow, hold your horses for a moment, before passing
judgment.
What the Multiplier Effect Means
To Us
When we overlay two or more sets of Bollinger Bands, we are actually seeing two
different sets of volatility.
Here's the best part of all…
If I were to ask you whether the total range of the EUR/USD would theoretically be
wider over an entire year, or over one week, what would your answer be?
One year of course.
Over the duration of an entire year, the EUR/USD would simply have more time to
trade up and down and would likely have a greater total range than just one week of
trading action.
The above concept implies, when all things are constant and markets are relatively
stable, short-term volatility should rest WITHIN long-term volatility.
In non-technical language, if you have two sets of volatility bands on a chart, a 50period and 14-period, for example, regardless of whether you are looking at one, two,
or three standard deviations, when looking at the same standard deviation setting for
14-period volatility bands, against the same standard deviation setting for 50-period
volatility bands, the 14-period standard deviation volatility bands should rest inside of
the 50-period volatility bands. (Again, only if markets are 'normal', or 'stable.')
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When volatility picks up though, which of the two bands will spike first?
The 14-period volatility bands will spike quicker than the 50-period volatility bands,
simply because there's less mass to move.
Do you see what I'm saying?
We're talking about volatility leading mass. The less mass an object has, the quicker
it can move. In terms of regular moving averages, a 14-period moving average is, or at
least should be, much more volatile than a 100-period.
Image this: You're standing in a Field in Kansas watching a herd of hippos graze in
the luscious grass… Suddenly an old truck drives by and backfires, startling the hippos
into a stampede.
Which of the hippos is likely going to be in the front of the pack, as the group starts
moving…
Most likely, the ones that prefer to graze on slim fast grass, over their big fat hippocolleagues.
Anyway, the point is when volatility is about to pick up and prices are about to
move, shorter-term volatility will likely start to bolt first, before the counterparts with
greater mass.
Why Do We Look For Volatility
Spikes?
When short-term VWAP volatility begins to spike outside of long-term VWAP
volatility, we should be on red alert that quick institutional money is 'on the move.'
The quick money, the guys, or computers, who are sharp, recognize a move is about
to ensue, and are putting their money to work. We can recognize this occurrence by
using volatility bands (Bollinger Bands) in conjunction with VWAP, to measure
volatility with dollar volume, instead of just price action (though we will use price
action in just a moment too.)
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Remember our previous discussion about Newton's Second Law of Motion, where
Force = Mass * Acceleration and Einstein's Mass-Energy Equivalence where E = mc2?
Don't worry about the math, just understand the theory…
For trending to ensue, there must be enough force to push the actual price
distribution to move beyond the present lateral range (support and resistance).
If a distribution has compressed, there is less mass to move, right? Right.
What we can then imply, is when a longer-term distribution has significantly
compressed (meaning mass is low/light) and short-term volatility spikes outside of
long-term volatility, we are seeing acceleration in action. Moreover, because the
longer-term distribution has shed mass (consolidated) the spike in short-term volatility
has greater probability of moving the longer-term volatility (and mass) with it.
We can restate Newton's formula as:
Mass = Force / Acceleration
Then, in terms of E = mc2, the energy required to keep a distribution in motion is
the mass times the speed of light (in a vacuum), squared.
The above math is not the most important point here… The critical component is
simply in understanding that the greater the spike of short-term volatility, outside of
long-term volatility, the greater the speed, or 'force' of the upcoming potential move,
assuming the longer-term distribution doesn't have too much mass already.
If you're a physicist, you may be thinking I'm confusing terms, however, for the at home
trader who does not have thousands to spend on coding, or technology, and/or the time, or desire
to study quantum physics, the concepts of force, acceleration, speed and energy are
interchangeable for our purposes here.
Simply put, the mass of a distribution cannot move without force. Moreover, there
is greater probability of force, when a distribution has less mass, over a bulky
counterpart.
In one of my conversations with Alvin Yu the CEO of ECTrader.net while I was in
China, I explained the above theory in markets…expecting questions.
Yu, a market genius and great friend, responded (to paraphrase), "Mark what you're
talking about is power."
I replied, "What?"
Yu added, "Have you ever heard of Bruce Lee?"
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"Of course, everyone in America has," I replied.
Yu suddenly popped his fist towards my face (yes, I flinched). When my heart
stopped palpitating, Yu's arm was extended straight outward, inches from my nose.
Yu asked, "What's wrong with this picture?"
"You're nuts?" I inquired.
"No," Yu said, "How can I hurt you now, with my fist totally extended?"
Alvin was right… Kung Fu and the market go hand in hand (in more ways than
one), as when one's arm is tight to their body, the greater the potential force that he, or
she can strike with. As the punch (arm) grows more and more extended, the less
power retained. There might be considerable force in during the extension process, but
as one's fist moves away from the body, the reality of the situation is that the hand can
only go so far. The distribution is in the process of extension (expansion) and there
comes a point where a fist can only go so far from one's body.
What the heck does all this mean?
Much like Kung Fu, when throwing a punch, one must eventually retract his or her
fist to regain power for another strike… Furthermore, while skinny people might be
able to punch quicker, most of the time, the larger dudes usually do more damage.
What I'm saying is short-term volatility strikes quicker, but when long-term volatility is
on the move, the blow will likely be greater.
No matter whether the puncher is big or little, skinny or tubby, guy or gal,
eventually the striker must pull back their fist…to reload.
Did I just say 'pullback'?
Yes I did. A pullback is a reload of power. In a moment, I'm going to show you
how to perceive a punch coming before you're upended on the chin by markets, and
how to tell when the striker has lost power and must reload. I will even show how to
distinguish when a counterblow has been served, causing a reversal of edge.
Again, what we're talking about is mass and force in terms of volatility, derived from
dollar/volume and price action.
So now, let's put the first part of the methodology into action… WVAV
volatility/energy…
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WVAV Volatility/Energy
I've supplied the code for WVAV, WAVE • PM and Two-CCI (making up Quad
CCI in two windows) at the end of the book. I have also supplied a template file (only
on the Website though) for WVAV, as well. To download the MetaEditor files, please
visit:
www.fxVolatility.com/volatility-illuminated-indicator-templates.html
In the following section, we will use WVAV volatility/energy opened twice on the
same chart. By this, I mean we will overlay two sets of VWAP volatility bands on one
chart.
The settings for the first set of WVAV volatility/energy (in MetaTrader) are:
WVAV (Energy)
10,000 ticks:
MA_Ticks
= 10,000
MA_Shift
=0
MA_Start
= 500
aa
= ********
MidBandVisible
= true
Bands Period
= 21
Bands Shift
=0
Bands Deviation
= 3.2
Color
= Red
1 = Dark Golden Rod
2 = Black
3 = Black
4 = Black
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Overlaying a second set of WVAV volatility bands, please input the following
parameters:
WVAV (Energy)
5,000 ticks:
MA_Ticks
= 5,000
MA_Shift
=0
MA_Start
= 21
aa
= ********
MidBandVisible
= false
Bands Period
= 10
Bands Shift
=0
Bands Deviation
= 3.2
Color
= Red
1 = Red
2 = Red
3 = Red
4 = Red
After you have the files and template installed in the proper folders, and are
running MetaTrader, please make sure the above settings are correct, while also
checking to be certain the indicator parameters are selected as well.
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Also:
1. In the Visualization tab of the indicator, please make sure: "All
Timeframes" and "Show in the Data Window" are checked for both VWAP's.
2. In addition, in the Common tab, please make sure the "Allow DLL
Imports" and "Allow External Expert Imports" boxes are checked for both, as
well.
3. Finally, in please right click on your chart and then select "Properties."
When the Chart Properties window comes up, make sure the "Show volumes"
box is checked, using any color you prefer.
When finished, your chart should look similar to:
Figure 10.7
Now, let's take a moment to dig into what we're seeing on the chart.
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First, I want to once again remind readers that what we are deciphering with WVAV
is how, where and why orderflow may be presenting itself (through the measurement
of volatility, by way of standard deviations) within currency markets…
What we are not doing is simply looking for brainless 'red line crosses blue line'
signals.
Figure 10.8
Understanding markets requires some human interaction and common sense.
Please apply both liberally.
Figure 10.8 shows the compression and expansion of 5,000-tick VWAP volatility,
and 10,000-tick VWAP volatility, as denoted by the arrows I have drawn, following the
lighter colored inner section of the chart.
You will immediately notice expansion follows compression, follows expansion,
follows compression, follows expansion, etc…
The chart clearly shows that when short-term VWAP (the more jagged, and usually
inner, of the two volatility bands) is expanding, we see more directional price action
than during moments of compression…
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Figure 10.9
Also, please take special note of the three expansion sections I have marked with an
'E' on the lower portion of the chart and the three frames I have marked with a 'C' for
compression.
As you likely see, expansion does not necessarily always mean 'breakout', rather,
expansion means 'price moving' in the range too.
What's more, please also notice that in the first section (on the far left), 5,000-tick
VWAP traded outside of 10,000-tick VWAP, kicking off the first stage of the overall
(though mundane) bullish rally.
What's interesting about this first pane, is we clearly see that when 5,000-tick VWAP
compressed back under 10,000-tick VWAP on the topside, a quick pullback to the
10,000-tick VWAP mean, immediately ensued.
Can you identify 'compression' and 'expansion' in terms of energy expended and
stored? Please take a look at the following 30-minute chart of the EUR/USD and
attempt to do so…
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Figure 10.10
What we see is the greatest directional 'bursts' came (coincidentally, wink - wink)
when 5,000-tick VWAP expanded outside of 10,000-tick VWAP, after a period of
compression.
Also coincidentally (or not!) in every occurrence where 5000-tick VWAP volatility
compressed back below 10,000-tick VWAP, the EUR/USD experienced a pullback to
the mean.
What's more, just a little over the half-way point on the chart (from left to right), you
will notice that when the EUR/USD fell below the mean of the 5,000 and 10,000-tick
VWAPs (with the 5,000 tick VWAP mean also briefly dropping underneath the 10,000tick VWAP mean), the EUR/USD never actually 'touched' the 3rd Standard Deviation
of the 5,000, or 10,000-tick VWAPs on the downside.
Here's what we know: Through statistics, there is a 99.7% probability will rest
within three standard deviations of the mean… We see the aforementioned empirically
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proved on our charts, as virtually all of the data sits within 3-standard deviations of the
mean…for both 5,000 and 10,000-tick VWAP.
However, when the EUR/USD tagged the 3rd-standard deviation of the 5,000 tick
VWAP, the pair pulled back to the mean. We basically know there will be times when
a pair touches the 3rd-standard deviation, but should not trade outside of it for
considerable time. What's more, we also know the instance of a pair 'touching' the 3rdstandard deviation is usually followed by a quick pullback to the mean, before the pair
travels higher…
We also know when a pair touches the 3rd-standard deviation, above or below the
mean (especially on shorter-term periods), the pair most often continues in the
direction of the 'touch', after pulling back.
Why?
Because if I am touching the 3rd-standard deviation of a short-term volatility range,
I am signaling that price/dollar volume pressure is experiencing 'quick pop' anomalies
on the side of the standard deviation touched.
The decline in the EUR/USD under both means – and the lack of the pair's ability to
'touch' the 3rd standard deviation on the downside – signals there just isn't enough
volume/dollar pressure to push the pair to a point where it 'touches' a 'distribution
outlier', i.e. the 3rd-standard deviation.
What this means to us is that if a pair fails the mean moving downward, but then is
not able to 'touch' the 3rd-standard deviation on the lower side…and then crosses back
above the mean in the previous direction, volume/dollars flowing into the currency
pair at that particular moment, are clearly bullish.
In the case of the EUR/USD (shown again in Figure 10.11), when the pair failed the
mean, there was not enough volume/dollar drive to push the pair into the lower
volatility band, and thus, indicated a bullish bias.
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Figure 10.11 - Repeated
Nothing in any market will ever travel straight up, or down, so we HAVE to expect
pullbacks, while also actively seeking to understand why and how they occur.
Figure 10.11 also shows when the 5000-tick VWAP was trading above 10,000-tick
VWAP, the instance was telling us short-term dollar/volume was indicating buying
momentum, and vice versa for the 5,000-tick VWAP trading below the 10,000-tick
VWAP.
Some of the best possible trading opportunities come when 5,000-tick VWAP is
trading above 10,000-tick VWAP and the 3.2-STD volatility bands have compressed,
meaning short-term volatility has contracted underneath long-term volatility...
Then, when the 3.2-STD 5,000-tick volatility bands expand outside of 10,000-tick 3.2STD volatility, we know we are precisely in the occurrence of short-term volatility
expansion, whereby price action should follow.
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In short, institutional order flow is buying, at least in the near-term. The opposite
would be the same for occurrences where 5000-tick VWAP has fallen below 10,000-tick
VWAP.
Overall, what we’re looking for are high probability instances of institutional order
flow showing signs of follow-through, while attempting to eliminate occurrences of
taking positions when there is no hope of trending, as seen through short-term
volatility compressing.
What I'm saying is when short-term volatility is moving inward, prices simply
cannot trend.
Thus, when we see 5,000-tick VWAP volatility fall back beneath 10,000-tick VWAP
volatility, we should be ready for consolidation and/or a potential reversal.
By using WVAV (mapping distribution width/mass outliers), we are able to keep a
close eye on volatility expansion and compression, thus taking positions during high
probability moments of trending, while also staying out of markets during moments of
consolidation. By doing so, we are stepping into the shoes of institutional momentum
and letting go of the 'old technical indicators' (like stochastics) that really don't work on a
short-term basis (consistently) anyway.
With everything that we have just covered, we will now enter into a discussion
about what institutional trading is really about, and the theory behind sell side order
flow…
Retail traders hardly ever take time to consider the true reality behind what order
flow is and why it occurs in the first place.
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CHAPTER ELEVEN
The Philosophy of Orderflow
and Markets
I hope the picture surrounding volatility/probability and the mass of distributions
is becoming clear… Just in case there are still a few moments of misunderstanding,
let's take a moment to go over what's happening.
To start, by watching the compression and expansion of volatility, in relation to
intraday trading, we are seeing when and where order flow is picking up and starting
to taper. What we want to look for (on 1-minute, 5-minute, 15-minute and 30-minute
charts) are instances of 'energy compression' followed by an attack of the 10,000-tick 3.2STD by the 3.2-STD 5,000-tick standard deviation.
In terms of volatility/probability, we are really seeing is an instance of distribution
'expansion', or a 'punch of force' to get price moving.
We can take positions on a quick pullback of the first attack of the 5,000 -tick VWAP,
placing a stop about 20 to 40-PIPs below VWAP. We can then walk our stops up (or
down in the opposite case) with higher lows (or lower highs for a descending trend)
two bars behind, or a close opposite the 5,000-tick VWAP, or a compression reversal in
5,000-tick 3.2 STD VWAP back under the 10,000-tick 3.2 STD VWAP.
The longer we hold a trade the more willing we should be to give it up if (and
when) a compression reversal of 5,000-tick VWAP volatility (reverting) slipping back
inside 10,000-tick VWAP volatility occurs.
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When the first pullback ensues, if the volatility expansion has truly triggered
institutional buying or selling, 5,000-tick VWAP will generally hold the first test. In
addition, we should constantly be looking for head fakes, should NO significant
volatility expansion occur.
Moreover, when we see a tag of 5,000-tick VWAP, without volatility expansion
(meaning there is no energy behind the move), we can think about potentially taking a
contrarian position, looking for a mean reversion trade within the channel, or envelope.
However, if the mean reversion position is against a strong trend, it's probably a
good idea to stay on the sidelines.
Also, if I am in a winning position and 5,000-tick VWAP compresses back under
10,000-tick VWAP, though I believe there is still reason (fundamentally) to hold the
trade, I will seek a close on the opposite side of 10,000-tick VWAP before exiting.
My assumption here is if the move is real, the institutional guys will begin showing
up at 10,000-tick VWAP, so as to not miss a 'performance enhancing' fill.
The bottom line here is VWAP volatility/energy expansion denotes high probability
of trending to follow, while VWAP volatility/energy compression denotes high
probability of consolidation (energy reloading, otherwise known as lateral trading)
about to ensue.
There's more to the picture though… As I watch VWAP volatility expand and
contract, I'm continually asking myself, 'if I had to work an order for $40 billion right here,
would I take the position now, or would I wait?'
To reiterate, WVAV is NOT a 'red line crosses blue line methodology', what WVAV
is showing, however, is some insight into large order flow through dollar volumes
moving in and out of markets.
When WVAV volatility/energy is compressing, the instance is indicating a possible
reload of energy, also signifying larger players are taking a break to evaluate the
situation.
Even major funds aren't sure which way to trade all the time, and/or will only buy,
or sell in areas where they feel valuation permits such.
In addition, because of the Central Limit Theorem (which means normal
distributions should appear in smaller subsets of larger skewed data), we can also infer
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that because VWAP and regular moving averages are mobile, eventually the currency,
stock, commodity, whatever, will revert back to the mean.
The reversion occurrence I've just mentioned is an absolute empirical fact, as the
mean is mobile.
What I'm saying is because the mean is following price, eventually the currency (or
stock, commodity, etc…) will retrace VWAP. The question is: when?
The more data we're measuring, the longer price can stay away from mean;
however, eventually, price will return to the mean, because the mean is following the
price.
It's important to note that when trading equities, or other instruments where VWAP
resets at the end of each trading day, seeking mean reversion positions (based on
VWAP) on a swing trading basis is not always the best idea.
Why?
Because at the end of the day (literally), the mean resets and there is no more reason
(in terms of day-to-day VWAP) for the security to revert 'across the mean' than any/all
circumstances that caused the initial divergence in the previous session.
In terms of day-to-day VWAP, we're talking about a 'resetting' of mass each session.
Thus, for mean reversion on a longer-term basis, either a greater amount of VWAP data
must be studied, or another set of data like price action (data without volume), must be
taken into accord.
The issue at hand is on a daily basis, there are many various factors affecting a stock, or
currency.
(For a moment, we will focus an example on equities.)
Figure 11.1
Please take a moment to glance at Figure 11.1,
imagining the image as a 'topographic map' of
intraday price data (Stock XYX), based on the
factors affecting trading action.
Now, please image (for the sake of example)
Stock XYZ reported positive earnings today,
which have triggered buying in the stock. The
darkest regions of the map specifically highlight
earnings related buying, while the lighter sections
indicate buying due to earnings related news of another (though related) company,
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which reported yesterday. Both sets of news are positive, shown in the overall upward
price action (as denoted in the data above the flat plane, which is the previous session's
closing price or 'breakeven' for today).
Again, because earnings of the 'related' (highly correlated) other company were
positive yesterday, and the earnings of the Stock XYZ are positive today, both sets of
news entice investors to buy more than sell.
Clearly, because price is ascending today, VWAP would travel upward during the
session as well.
However, what happens if the two previously mentioned companies are tier two
stocks (meaning lesser market caps) than the sector leaders. Moreover, what if, a
highly correlated tier-one company reports significantly negative earnings numbers
tomorrow?
Because the tier one company likely has greater pull on the entire sector, the
positive news of the two smaller companies could fall victim to sector-wide selling,
based on the negative news of the larger, more highly coveted tier-one company.
What we're talking about is the larger gravity (weighting) effect of highly correlated
stocks, sector, index, market, or other financial instruments that could influence the
outcome of tomorrow's trading, over stock-specific news of today.
In short, because we are resetting the mean (VWAP) each session (in equities)
performance of the benchmark must be evaluated by what is taking place today, and
only today.
What I'm saying, is whenever we reset the mean (the same would hold true for a
5,000, or 10,000 tick reset in Forex), we must stop, take notice of the event and
reconsider the factors pushing, or pulling on the instrument in question.
To rephrase, when VWAP is reset, the instance of price moving away from the
benchmark would not necessarily be a specific derivative of mean divergence, or mean
reversion from the previous session. Because VWAP was reset, the occurrence would
really be pure divergence, based on the simple fact that the benchmark was just re-set
to zero.
The longer VWAP is 'running' however, the greater the probability that price will
eventually revert to the mean, based on the concept that the mean is following the
price.
Where does all this lead us?
To a much needed discussion of the term 'benchmark.'
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Most Retail Traders Never
Consider the Term 'Benchmark'
To some, it might feel as though the following discussion should have come earlier
in the book. And while (arguably) that may be so, I decided to save it for when we
were already knee deep in VWAP, as I believe already having the visual picture of
what VWAP is (in your mind), will help the following concepts come through more
easily.
Over the following pages, impatient traders will likely scoff at the information and
quickly breeze over the concepts of order flow and benchmark trading.
However, I would like to mention the next few pages might be the most important
in this entire book…
We must have a better understanding of who is who in trading (meaning who is
buying and selling) and how and why such influences volatility.
The following pages are critical for anyone seeking to move beyond simply being an
'average retail trader,' to truly finding a greater understanding of intraday volatility.
I've spent many hours attempting to understand why retail traders fight –tooth and
nail– understanding the larger 'paradigm' behind institutional order flow, versus the
cowboy jockey directional 'give me a quick and easy brainless technical indicator' mentality
most at-home traders embrace.
In the fall of 2008, I believe I (partially) found the answer…please allow me a
moment to tell you the story…
Over the final few months of 2008, my trading was suffering… I was having trouble
diagnosing the issues causing the poor performance, as it seemed the more I looked,
the less I came up with in terms of answers.
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In the end, I found two main catalysts for the temporary deterioration in my
trading.
First, the market had changed and I hadn't.
I was still working on developing new models to compensate for the excess
volatility brought on by the financial crisis, while also attempting to compensate for the
moment-to-moment excess volatility of retail traders, both of which had begun to
surface in July.
I was not really having any trouble perceiving the larger direction of markets, but I
constantly found myself losing intraday.
In short, I was developing new volatility models in a rough market and I was
paying the price for deploying new concepts in real time, with real money.
My Forex Force trading service on Wall Street Rock Star finished the year up over
1,000-pips, but November and December were brutal.
There's another piece to the story here too…
In late October of 2008, I traveled to one last U.S. speaking engagement, before
leaving for China…
During a break, one of the attendees found me outside, and we began to chat… A
few minutes into our conversation the chap said, 'this is incredible information
(referencing my delivery of common sense fundamentals), but can you just give me something
easy I can just make money with today.'
To date, almost no other comment by any reader, subscriber, or audience participant
has ever messed with my head more. I was so up-ended by the comment; I had trouble
returning to the room to finish the talk…
It took about three months to figure out why the comment was disturbing… What
I've come to realize is:
When it comes to educating others, all my time and effort…years of learning… All of my
time preparing a clear, concise, cutting-edge understanding of fundamentals within currency
markets is/was a waste.
Wasted because most people do not want to know anyway.
I realized that most retail traders only want 'blue line crosses red line' signals hand
delivered, gift wrapped, without ever truly even lifting a finger to learn about markets,
or the indicators they're trading from.
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From that day, I lost all of the wind in my sails to run the trading service, and while
my new models were still suffering in deployment, I had lost the desire to trade too,
which was really bad, because trading is my bread and butter.
In January of 2009, I shut the service down and I will never spearhead another
intraday 'trading specific' service ever again.
We're planning on launching a new live trading room and a professional trading
research service on WallStreetRockStar.com this year, but neither will be an intraday
trading service telling people when to buy and sell.
After months of brooding about the audience participant's comment in the Fall of
2008, I realized I needed to let go of the service, because the performance was suffering
and I just wasn't into it anymore.
What I also realized was that most retail traders don't want to learn the nuts and
bolts of what truly moves markets… When I let go of the comment and concluded that
this will likely be my last book…I again found my passion for trading…
What I also come to terms with is an understanding that most retail traders just can't
see the value in understanding fundamentals. Moreover, because applying
fundamentals to intraday trading takes a significant amount of effort, it's easier to just
look for signals from a MACD, or stochastics, or whatever else someone said works
well. But regular technicals (without a rock solid understanding of why what's
happening is really happening) only sets traders up for failure.
In the end, I ask you to please turn over every stone, including the forthcoming
discussion of buy side, sell side, benchmark, etc…
Sometimes the most important –and greatest– nuggets of information are found in
the most unassuming places, like the true foundation of the events occurring, not in
the outcome…the red line crossing blue line technical events.
Also in my drawn out explanation of why most retail traders never really consider
what, where and why institutional trading is happening…is simply in the question:
Why would retail traders be motivated to step into the minds of the big guys anyway?
After all, retail traders are trying to make money moving in and out of markets
directionally, always with a short or long-term bias.
Institutional traders, however, are thinking risk and performance.
It's not the retail trader's fault really that he or she has no clue about what's really
driving much of intraday action. After all, most of the information provided to traders
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regarding what to look at, why to look at it, and how to trade it, is generally flawed from
the start anyway.
Forex brokers aren't going to tell you, because most often they are in the business of
'broker/dealer' meaning they're taking the other side of your trade…
When we understand that much of intraday trading action volatility has more to do
with the term 'benchmark', over 'pick a direction', we begin to put the odds back on our
side.
I believe that if I were to ask 99% of the retail readers what the term 'benchmark'
means, most would say 'index', or something similar. Yes, indexes are 'benchmarks',
but for our purposes, we're looking for something different, something greater.
Benchmark –as we will use the term here, is the capacity of trading efficacy, by
which institutions and institutional traders are both: measured and paid.
What we're talking about is 'buy side' versus 'sell side' versus buying and selling.
One thing I know for sure is if I were to ask 10 retail traders (who have never traded or
worked for a financial firm professionally) what the differences between buy side, sell side
and buying and selling are, 10 out of 10 would get the answer incorrect.
It just is what it is…
We need to know though, to be the best traders we can be…
Mark Whistler
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BIOVAP Man and the Insanity of
Dr. Watermelon Stuffer
It is no secret; the business of trading is overcomplicated from the start…
For the retail trader who attempts to dig into understanding of how institutions
work, the door is seemingly impenetrable.
Because of such, there is a massive breakdown in the retail community's
understanding of what 'buy side', 'sell side', and buying and selling are.
Why should you care?
What we have to understand is that real trading is the actual application of
expectations to real markets.
Analysts analyze; however, traders apply money to reality.
The best analysts in the world often make the worst traders.
Why?
Because while they can perceive an outcome over the long haul, they have no clue
how to apply the information in the short-term.
When we truly attempt to understand how and why institutional traders are doing
what they are, and what they might do next, we're stepping out of the analyst fairytale
world and into the real battlefield of now.
The bottom line is, if we expect to succeed in trading we MUST take the time to
understand why what is happening today…is happening.
Why what is happening this hour, is happening this hour…
Why what is happening this minute, is happening this minute…
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We must step beyond simple technical and fundamental indicators and into the
minds and motivations of big order flow...to finally see 'beyond the curtain.'
Buy Side/Sell Side
Briefly, buy side is anyone who is trying to make money on the perceived
movement(s) of a financial instrument.
Conversely, sell side is anyone who is trying to make money on the people…who
are attempting to make money…on picking the direction of a financial instrument.
Moreover, buying and selling is something anyone who wants to play the game
must do…
Both buy side and sell side…buy and sell.
Perhaps the only people who don't
actually buy and sell (in the game of buy
side/sell side) are sell side analysts who are
merely telling people what to buy and sell, in
an attempt to get more people to buy and sell.
Buy side analysts, are often making actual
recommendations to buy or sell, which a fund is
actually taking action upon.
As Larry Harris notes in the book Trading
and Exchanges, "buy side traders are
investors, borrowers, hedgers asset
exchangers and gamblers."
(I hate to say it, but most retail traders
(daytraders and Forex traders specifically)
fall more under the 'gamblers' category.
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An important distinction differentiating buy side and sell side Harris points out is, "The
Trading industry has a buy side and a sell side. The buy side consists of traders who buy
exchange services. Liquidity is the most important of these services. Liquidity is the ability to
trade when you want to trade."52
In terms of being 'retail' (a buy side trader, just like a fund trader), you are paying
commissions for the ability to guess whether a currency, stock, or commodity is going
up, or down.
You are paying for liquidity, which your broker is providing. The broker is 'sell
side', as he is providing you with the means to place orders.
Also of important note, Harris points out the concept of 'movement of current income
into the future.'
Buy side traders are really using what they have now, in an attempt to realize
another value (hopefully greater!) in the future. One cannot trade with more than they
have now, as even with margin, once what you have now is gone…you have nothing.
One of my favorite sayings of all time is from Warren Buffet who states, "zero times
anything is zero."
For example, as a 'buy side trader', you can leverage $10 into $100 (10:1 margin) in
an attempt to make even more money directionally in markets, but if you're wrong,
and your original $10 disappears, you have nothing.
In detail, sell side is/are the people/companies providing buy side with liquidity
and/or services to effect and/or improve transactions.
In short, institutional traders who are 'moving orderflow' are sell side traders.
Here's what's important to note, sell side traders can both work for a corporation, or
remain independent, utilizing the sell-side services of other exchange related
companies.
What I mean by this is, some independent traders actually own a seat on an
exchange, where they effect transactions to work orders for buy side traders.
However, because they are not their own clearing firm, they must utilize the sell
side services of another firm to achieve liquidity.
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Basically, when sell side is moving orderflow, buy side individuals or funds are
using their services, and are either willing to pay a higher price for their tenured
trading ability to work large orders (usually because of long-lasting relationships), or
whatever 'edge' the sell side firm, or trader brings to the table, in terms of helping the
buy side achieve a more prosperous fill.
These guys are a type of sell side middle-men, and are acting in a 'broker' capacity,
but utilize another firm (a dealer), to clear the actual trades.
Really, sell side means dealer, broker, or 'duel
traders.' It is also important to note, exchanges are in
the mix as well, competing with brokerage houses to
'arrange trades.'
Finally, in our discussion of sell side (and buy
side, in terms of definition), it is also important to
note (as Harris points out); sell side ONLY exists
because the buy side is willing to pay for their
services.
Now that we've covered buy side and sell side…a
few readers may still be inquiring: Who does the
buying and who does the selling…buy side, or sell side?
Both. Both buy side and sell side…buy and sell.
The terms buy side and sell side are simply
definitions of the 'capacity' of buying and selling
motivation.
The 'capacity' of buy side buying and selling is to
make money on the movement(s) of financial
instruments. The 'capacity' of sell side buying and selling is to provide buy side with
liquidity, or to create 'price improvement' on large orders.
Easy enough right? Right.
As I write, I'm wondering if readers are now asking what's the larger point of this
entire discussion – of buy side and sell side? If you are, I applaud you. The larger
picture is exactly within the question itself– the larger picture…is 'the big picture' of
why volatility exists within intraday trading in the first place, but it seems to me that
almost no retail traders actually 'get it.'
See, most retail traders consider the 'big picture' to be their monthly charts, or 'those
boring fundamentals.'
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However, in terms of intraday volatility, the big picture is really within institutional
benchmarks. When we understand institutional 'benchmark trading' we will also find
a greater understanding of:
1. Why retail technical indicators are built for failure…
2. Why most retail traders lose…
3. How the big guys perceive information differently…
4. Why having an institutional mindset is so important…
5. How we can use volatility, probability and benchmarks (like VWAP) in our own
trading to take advantage of potential institutional order flow pending….
I would like to take a moment to quote John Pinney (JP Morgan) from the book,
Coping with Institutional Orderflow (Robert A. Schwartz, John Wiley & Sons, 2007) who
stated, "I will do my best to convey the essence of the research we recently completed
on the cost of dynamics associated with institutional orderflow. To a retail trader, the
stock exchanges look like a vending machine. An order is placed, the delivery is made
and the execution comes back. The broker has completed his or her job, often within
seconds."
Pinney is right, the retail trader DOES believe his, or her platform is nothing more
than a vending machine…
Order in, position in, order in, position out.
It is here that we further answer the question of why the retail trader never even
knows to consider the mindset of institutional order flow…
Pinney goes on to state, "But this is not the case for the institutional trader. As we
know, the order size – the 'peg' of institutional trading interest – is much larger than
the 'hole' size of the exchange process.
PLEASE READ CAREFULLY:
Take a moment to ponder what Pinney has just described as the concept of
institutional orders being larger than the 'hole' of the exchange process…
If you take one thing away from this entire book…
Please take the following words:
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Institutions must constantly break up large orders into smaller
chunks; otherwise, they would constantly be attempting to shove a
watermelon through a muffler.
Not only would the people around them notice, but also, the event would be both
sloppy and ineffective…
In normal circumstances, sell side traders are able to dice the watermelon (large
order) and discreetly slip the pieces into the market one-by-one (iceberging).
However, what happens if the car (price) the muffler is attached to…is about to
leave the parking lot?
Even institutional traders are sometimes caught off-guard and are forced to start
shoving the watermelon through…you know what.
What we're talking about is volatility…derived from big buy side politely asking
sell side to insert watermelon into mufflers, all day long.
Sell side is Dr. Watermelon Stuffer and all day long he's receiving orders from Boss
Big Bank (buy side).
Moreover, what if he's been told to get the watermelon in the muffler 'or else' and
the car starts to move? You guessed it; he might have to run after the car, trying to
shove the whole watermelon (or pieces of) in to the muffler, before the car (price) gets
away completely.
What we are talking about is the occurrence where markets begin moving (on low,
or high volume) and are seemingly propelled by constant buying, or selling.
Now, assume you are Dr. Watermelon Stuffer for a moment and you're a little
smarter than most…
You know the driver is 'just making a delivery,' and he will actually be back in about
15-minutes… It's a good thing you know too, because you still have half a watermelon
to cram into the muffler.
Of course, when the car pulls back into the parking lot…you would start cramming
again, before the car pulls out another time. Big Boss Bank is paying you on your
performance…based on how much of the watermelon you can get into the muffler, as
neatly as possible, before the car pulls out of the lot. If the car pulls out of the lot and
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you've been able to neatly (and discreetly) dice the entire watermelon and insert it into
the muffler, you will be paid handsomely.
But what if you suddenly figured out you'd goofed and crammed all of the little,
neatly sliced pieces of watermelon into the wrong car?
It's going to be ugly trying to get the watermelon back out.
What we're talking about is volatility, when the big guys are wrong.
What if, you crammed the whole watermelon into the muffler and it is the not only
the wrong car, but the driver just got in?
Roll up your sleeves, because things are about to not only get messy, but frantic, at
the same time.
What we're talking about is volatility.
What if you have an absolutely massive watermelon to stuff…but you know the
driver's schedule, and thankfully he will be back 30-minutes after each time he leaves
to make a delivery…
Each time the car pulls out of the lot, you'd likely just take a seat and wait for him to
come back, to begin inserting more of the watermelon into the muffler.
What we're talking about is the occurrence of institutional traders buying at, or near
VWAP (or other benchmark) and why they don't often chase price…
Unlike the retail 'breakout' trader, the institutional watermelon stuffer knows the car
will be back…
So where is the retail trader trading in this whole event of stuffing watermelons
into mufflers?
He's standing over on the curb, waiting for the driver to pull by, to see if he can
exchange a couple quarters for a dollar bill…completely oblivious to the whole stuffing
of watermelons thing, happening just a few feet away.
Fact is, when we understand what's happening on the institutional sell side, we
suddenly understand 'why that really weird uptight guy standing behind the car – is
always holding a watermelon.'
However, to see Dr. Watermelon Stuffer, we have to wear special glasses, because
there's one thing I forgot to mention… Dr. Watermelon is invisible most of the time.
To see him, we have to wear special volatility / probability, VWAP, TWAP, LHOC
benchmark glasses.
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And we're not always going to be able to see him, even when we think we can, but
the longer we wear the glasses, the better we will become at spotting Dr. Watermelon
Stuffer, even when he's mostly transparent.
(By the way, these are special cars…that even when the mufflers are crammed with melons,
the engines do not cut out… Things just run differently in Financial-Market-Land.)
Here's the thing about almost all of the 'other' retail traders though… They're
standing around on corners, all with the same quarters, trying to exchange their change
for the same dollars…
They're easy to spot too, as they're all wearing the same fancy pants and 'blue line
crosses red line' MACD, stochastics, Fibonacci, moving average, relative strength
[whatever] jackets.
But they're all oblivious to the real game.
The real game isn't even about quarters and dollars, it's about cramming
watermelons into mufflers, before the driver leaves with the car in one direction, or
another. Fact is, all of the retail traders (in their fancy technical analysis jackets) never
even understood the real game from the start, which is exactly why they will always be
exchanging quarters for dollars on corners.
However, because they're all just standing there, obvious to the world, money in
hand…eventually, they all get mugged too.
Many retail traders believe they have an edge though…
They've got a little buddy, who happens to be real fast at math, and can regurgitate
fancy pants signals all day long.
He tells the retail traders (who think they are smarter than the collective whole) when
other retail traders are about to change jackets. Sometimes his fancy pants signals work,
but really, he's missed the whole game too.
And eventually, when the driver changes schedules, or routes…or when Dr.
Watermelon Stuffer changes his entire outlook on his watermelon stuffing process, or
even worse, gets a new tool to stuff watermelons with, the retail trader's little buddy
(FYI, his name is EA, for Expert Advisor, but his Mom calls him Black Box System) starts
to get it wrong… One more time, the retail trader is just stuck there, standing on the
corner with his little pal, getting mugged (again!), scratching his head…
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See, the whole game is really about the watermelons and the driver. Concerning the
driver, it's about when he's going, why he's going, and where he's going…
While the car is 'price', the driver's name is 'fundamentals'.
Let me tell you, since the driver has so much on his mind, he changes his
philosophy and outlook daily…
Sometimes though, he gets an idea in his head…and he just keeps on going, until
he's out of gas.
In rare occurrences, the retail trader actually really attempts to figure out the
driver's schedule, but the occurrence is rare.
Regardless, retail traders fail to understand the money (the real money) isn't just in
figuring out the driver's schedule, but ALSO in knowing (and seeing) Dr. Watermelon
Stuffer's probable plan too.
For the retail trader, the real money is in betting other's (who are watching the car
too), when the driver will come and go… Moreover, the intraday trader who has the
special x-ray glasses though, knows to only bet when Dr. Watermelon Stuffer is at work
behind the car, because when Dr. Watermelon Stuffer is furiously in motion, the car is
about to move.
Volatility and probability help determine when the car is about to move, how far it
might go, and when it is coming back.
Benchmarks are knowing where Dr. Watermelon Stuffer may begin stuffing, or start
retrieving his crushed fruit, or used in conjunction with volatility and probability,
where he might just decide to sit the whole game out for awhile.
Fundamentals tie the whole thing together.
Typical technical analysis (used on its own) is a joke.
Remember the first chapter about Superman wearing his underpants on the
outside?
The retail trader who understands Dr. Watermelon Stuffer is: BIOVAP Man –
Benchmark Institutional Orderflow Volatility and Probability Man, and is a superhero
for sure…even if he looks a little goofy.
He wears his underpants on the outside, and he sports x-ray glasses.
Dr. Watermelon Stuffer tries to make fun of him, but BIOVAP Man just smiles, nods
and replies, "Whatever melon-boy, just keep on stuffing and everything will be alright…"
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CHAPTER TWELVE
WAVE • PM
Whistler Active Volatility Energy
• Price Mass
As we enter Chapter Twelve, there are likely some questions still remaining on how
WVAV and order-flow come together in the larger picture at hand.
As there should be…
Over the following pages, however, we will begin to tie all of the pieces together in
one large cohesive model, for traders to utilize as they navigate markets daily.
With all of the aforementioned in mind, please put any questions on the subject of
Dr. Watermelon Stuffer and BIOVAP Man on ice for a few moments, as we cover the
final piece of the larger whole: WAVE • PM, or Whistler Active Volatility Energy •
Price Mass.
In our previous discussions of mass, we know two things:
1. Mass is a larger component of price movement, via distributions, seen through a
Newtonian lens where: Force = Mass * Acceleration, or Mass = Acceleration /
Force.
2. The larger the mass, the more difficult an item is to move. Conversely, the less
mass an item retains, the easier it is to not only spur into motion, but keep in
motion, as well.
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With common sense physics in mind, it is easy to begin to understand why
unforeseen volatility sometimes surfaces within almost any market, especially in terms
of 'head fakes'.
When an equity or currency pair is staging a supposed breakout, but there is simply
too much mass to be moved, it 'just makes sense' that price would fail to continue
upward, or downward…and thus, fall back into the previous range.
What we are really talking about here is the compression and expansion of energy,
in terms of mini distributions.
If a distribution is already at a point of maximum expansion (too much mass), the
likelihood of continuation (trending) into a higher or lower range…is not very likely.
As a picture tells a thousand words, it may be easier to soak up the previously
mentioned concept with an actual chart…
Figure 12.1 shows the EUR/USD on an hourly basis, where I have drawn a set of 50period 3.2 STD volatility bands, to show the 'outlier' points of the distribution.
As you can see, during the recent rally, the 50-period distribution was 'expanding' in
width, or in other words…mass. As the EUR/USD traveled into the 1.4030 area, the
50-period mass became too 'heavy' for the pair to continue upward…
Thus, as the consolidation (and compression of the 50-period 3.2 volatility bands)
shows, the pair traveled sideways, thus allowing the total mass of the distribution to
'compress' for another move.
The solution to the problem of being able to readily 'see mass' within a stock,
currency pair, or commodity? The solution is rather simple; however, like most
concepts in Volatility Illuminated, the theory was the most difficult part to unearth…
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Figure 12.1
The theory behind measuring the mass of subset distributions is simply to visually
'map' or identify the total width of both short and long-term distributions, through a
value converting mass into an easily recognizable/understandable format, like an
oscillator.
Thus, what we have taken two sets of Bollinger Bands (volatility bands) and simply
normalized the total width of each, in range from 0 to 1.
What this means is with our new 'gauge' (imagine an RPM gauge for an engine) we
know the closer the oscillator is to 1, the more mass a distribution has, and the less
likely the chances of a continued up, or down move, without some sort of consolidation
'cooling' or 'compression' of energy first.
In the following image (Figure 12.2), readers will notice I have added the WAVE •
PM oscillator in the bottom window…
Please observe that there are two lines in the oscillator, one measuring a 50-period
distribution, and one measuring a 14-period distribution.
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Obviously, the 14-period line is the more jagged of the two, as we are measuring
less data.
Below the 0.5 oscillator level, mass can said to be consolidating, while a move above
the 0.5 is generally marked with a period of distribution expansion, or extended price
movement.
It is VITAL to note that the WAVE • PM does NOT give any indication to
direction whatsoever; rather, the oscillator is a gauge of potential energy left within a
distribution's expansion cycle…
If price is moving to the downside and WAVE • PM is moving up, the event simply
means there is more 'gas' left for an extended move…
Stating the aforementioned another way, if price is moving downward and the 14period WAVE • PM is traveling upward; the occurrence indicates the 14-period
distribution is widening out, or releasing energy.
Conversely, if price is moving upward and the 14-period WAVE • PM (for example)
is traveling upward, the occurrence indicates the 14-period distribution is widening
out, or releasing energy.
It doesn't matter whether price is moving up, or down, if WAVE • PM is moving
up, the distribution measured is 'expanding' and/or releasing energy. If WAVE • PM
is moving down, the distribution measured is 'compressing', or storing energy.
If price is moving upward and WAVE • PM is moving upward, the event simply
means there is more 'gas left' in the move. When WAVE • PM is between 0.7 and 0.9,
the event is similar to the RPM gauge on your car showing about 2,800 RPM's, or
maximum pull…
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Figure 12.2
In the above image, you will notice when short-term WAVE • PM is descending; the
EUR/USD is in phase of consolidation. Conversely, as noted in the three right-most
arrows, when short-term WAVE • PM starts to move above the 0.5 mark, the
EUR/USD begins breaking out of the relative range to the downside…
As we've already covered in the book, we know that when short-term volatility is
compressing, versus longer-term volatility, the changes of trending a slim. However,
when short-term volatility is torridly expanding, the occurrence is telling us prices are
on the move and short-term volatility is attempting to push longer-term volatility (or
the longer-term distribution) upward, or downward.
Again though, WAVE • PM does not provide an indication of direction, rather, the
indicator shows whether a move presents high probability of follow-through, or not,
based on how much 'mass' there is to move. It's just common sense that a distribution
with less mass is easier to move, than a distribution with a significant amount of mass.
Now, please look at image 12.3, for more insight into the WAVE • PM indicator…
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As you will notice, in every instance the short-term WAVE • PM mass line (denoted
as the thicker of the two indicator lines) falls, the EUR/USD experiences a period of
comparatively lateral trading, or a pullback in the relative range. WAVE • PM is
visually identifying the 'compression' of the short-term distribution within the larger
distribution. Just FYI, we are mapping a 50-period 3.2 STD and the 14-period 3.2 STD
in the example here.
However, it really would not matter if were mapping 1.2-standard deviations, or
3.2-standard deviations, as both show the expansion and compression of mass.
What you will also notice is in the first part of the move up, the longer-term
distribution was in an 'expansionary' phase, but then started to compress while the
EUR/USD continued the final phase of the upward movement.
Why?
Because when a trend first begins, the multiplier effect in the standard deviation
formula causes both bands to widen out… However, for price to continue in one
direction (up, for example) the bottom band must eventually turn around and begin
moving upward with the price…
The two bands cannot move away from one another infinitely, as the 'lower' third
standard deviation must (eventually) move with the distribution, upward, as noted in
the example here. Thus, if a trend is real, the longer-term distribution (again, we're
measuring the longer-term distribution via 50-periods of data here), will eventually
turn upward and as the lower band pulls up, will show consolidation in the WAVE •
PM indicator.
What this means is two things:
1. During the initial expansionary phase of a trend, both long-term and short-term
WAVE • PM should witness upward movement.
2. As the top of a trend nears, longer-term WAVE • PM will begin to turn over and
'consolidate.' By the term 'trend', I am referring to the 'cycle' of the relevant trend
either up, or down.
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Figure 12.3
What we know from all of the above is our greatest probability entries (to capitalize
on trending) occur when both short and long-term WAVE • PM are below 0.5 and are
beginning to move upward.
To active traders, WAVE • PM below 0.50 indicates that energy of both short and
long-term distributions has compressed, and we currently are sitting in the greatest
possible moment for a potential breakout (or breakdown) to be followed by trending,
via energy expansion, because both short and long-term distributions have little mass
to move.
Again, the lesser the mass, the greater the probability of seeing 'follow through',
once order flow begins pushing…
What's more, as we previously covered in Chapter Ten, once a stock, or currency
begins ascending, we can view the event as the 'car' beginning to move out of the
parking lot.
If Dr. Watermelon Stuffer did not previously have all of his melon in the muffler,
chances are, he's going to get a little messy if he thinks the car is about to pull out of the
lot. Henceforth, the instance of 'quick acceleration', often appearing when a pair
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initially breaks above (or below) a consolidation range, seen through a breach of
support, or resistance.
To reiterate some of what we have just covered, when WAVE • PM is declining
(especially noted in short-term WAVE • PM falling) the distribution is experiencing
consolidation and thus, lateral trending will likely occur.
When WAVE • PM is witnessing a period of expansion (upward movement), the
greater the likelihood of continued trending, especially if the WAVE • PM indicator is
rising out from underneath the 0.5 area.
WAVE • PM, WVAV and Quad CCI
Now, pulling everything together, we will see the 'perfect setup', which wellinformed currency traders (and even stock, commodities and futures, etc…) will want
to look for… The following example shows a downward move; however, such is
precisely what we look for in an up-move, as well…
In the following image of the EUR/USD, traders will notice the pair had
consolidated near the 1.4080 to 1.4120 area, and was threatening a break…
Most important, traders will notice both the 50-period and 14-period WAVE • PM
lines were trading just below 0.5, as the EUR/USD first broke support in the 1.4044
area. Confirming a potential down-move, 100-period CCI was just falling into the
'Containment Zone', meaning that it was falling back below the 1.25 standard deviation
area, on the way back to the mean. Next, traders will also notice 50-period CCI had
already also broken into the Containment Zone, while short-term 5,000-tick VWAP 3.2STD volatility bands (dashed lines) were expanding outside of long-term volatility, as
measured by 10,000-tick VWAP 3.2-STD (solid black lines) in the price portion of the
chart.
The chart was telling us, 'short-term volatility is spiking outside of long-term volatility',
while also indicating mass had 'compressed' enough that probability of trending was
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high. In other words, price distribution mass had compressed to a point where a burst
of downside trading action could easily get the ball rolling… And it did…
The EUR/USD quickly fell over 100-PIPs, before the WAVE • PM 14-period line
turned over to 'compress.'
At the same time, short-term VWAP volatility pulled back inside of long-term
volatility, thus giving us further indication that the EUR/USD was about to enter a
period of 'pullback', or consolidation.
During this time of consolidation, not one of our CCI's really gave us much
indication of the pullback happening, other than the 14-period, which rallied from
below -100 almost into the 0-line, before failing again.
Why?
Because CCI only measures prices outside of the 1.25 standard deviation area.
However, price consolidation on shorter-term time periods can occur, without longerterm CCI breaking back below the 1st-standard deviation. The occurrence really
indicates the longer-term distribution is still on the move, however, in the short-term, a
pullback to the mean is in store.
The savvy volatility/probability trader, however, was cognizant of the pullback, as
noted in the 14-period WAVE • PM falling short of the 0.9 line, declining down into the
0.55 area…
Because short-term mass had compressed, smart volatility traders would have
begin looking for another leg down in the move.
Coincidentally (or not), during the pullback, the EUR/USD rallied right up into
5,000 and 10,000-tick VWAP, where it again failed.
Why the failure at VWAP?
Because if a move is for real, the benchmarks are precisely where Dr. Watermelon
Stuffer will begin 'cramming his watermelons into the muffler', to achieve the best
possible benchmark performance fills, for the day. The institutional trader knows that
should the EUR/USD drop again (which it did), he needs to execute his orders 'better
than' VWAP (which he did), as VWAP drops with sustained selling. As VWAP
declines later in the session, his previous fills into VWAP will then show 'better than
VWAP' performance.
Do you see how everything we have covered comes together?
What we're really talking about is watching 'mass' for 'viability' of a sustained move,
and then watching for the precise points during the move where Dr. Watermelon
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Stuffer must begin wading into markets in order to achieve the best fills possible–
where his performance will be measured, in relation to VWAP. A pullback to the mean
(VWAP) is to be expected in any ascending, or descending move… However, when
longer-term CCI is indicating that the instrument is still trading outside of the 1ststandard deviation, or below the mean, we know the trend is still in effect. Then, if
mass (as measured through WAVE • PM) still has room to widen and short-term
volatility spikes outside of longer-term volatility, we know to immediately take
positions with the trend, to capitalize on another bolt of price action.
Figure 12.4
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Again, we can look for true 'vigor' where a move starts and ends, through the
expansion of short-term volatility, outside of long-term volatility, and conversely,
where lateral trading (back to VWAP or a larger reversal) may take place, through
short-term volatility compressing back underneath longer-term volatility.
Moreover, in Figure 12.4, you will notice I have marked longer-term (50-period)
WAVE • PM as seemingly dangerous, when it was trading above 0.9.
What the occurrence meant to us was the distribution was too wide, meaning it had
too much mass, and the likelihood of consolidation, or a reversal was highly likely.
In the above case of the EUR/USD, exactly such happened, as just after the 50Period WAVE • PM line started to fall back below 0.9, meaning the distribution was
compressing, the EUR/USD experienced a rugged period of lateral/choppy trading.
Personally, during periods of longer-term distributions compressing (after a large
upward or downward move), I prefer to just sit out of markets and let the other guys
slug out choppy sideways trading…
Then, when both the 50-period and 14-period distributions have again consolidated,
I will look for short-term volatility spiking outside of long-term volatility (and a breach
of major support, or resistance), to take a position 'with the trend.'
In essence, we should refuse to take positions when 'mass' is too large and the risk
of mean reversion choppy trading is substantial…unless of course, we are specifically
attempting to take advantage of a mean-reversion type of position.
In the end, when we apply volatility/probability to the larger concept of subset
distribution mass compression and expansion, we not only are able to navigate markets
with incredible perception, but are able to transcend intraday volatility that kills most
traders.
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CHAPTER THIRTEEN
The Dynamic Movements of Subset
Distributions
Within the following pages, the concepts presented are intended to not only
challenge the reader's perception of traditional descriptive statistics and distributions
even further, but the greater awareness volatility and probability within markets as
well. Moreover, the application of volatility/probability to markets was actually
derived through countless hours of philosophical-reasoning behind the 'theory' of the
concepts at hand.
Beyond math, the principals within the final chapters of Volatility Illuminated are
intended to invoke fresh conversation about common perceptions of accepted
standards of price movements within markets.
It is the author's intention to show that both empirical and non-empirical events
within time, existence and markets are comprised of both normal and non-normal
distributions, whereby the identification of an imperfection within the smaller subset of
distributions surfacing in the larger skewed distribution of markets (and time) is
actually the 'imperfection of perfection' that must remain for time to persist, markets to
move, and stretching to the bounds of philosophy, to empirically prove some of the
toughest questions regarding price action, all at the same time. In essence, identifying
imperfection within subset distributions validates volatility and movement within
markets, time, and history.
Furthermore, the author will show that volatility within distributions is relative only
so far as probability -measured in standard deviations– infers information (and subset
distributions) can never maintain a static state. However, much like time will not cease
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to progress, neither will the movement of information affecting markets and life; thus
the traditional perception of risk probability and standard deviations as static…is
flawed.
Within distributions (and the outliers of volatility) resides variance, or the
probability of tails. However, when understanding that markets will never remain
stagnate, one comes to terms with the understanding that 'outlier variables' are actually
the pivot points whereby markets shift, prices move, distributions evolve and time
progresses.
Historically, participants have approached markets (in terms of descriptive
statistics) with the perspective that one may continually rely on mean-regression
empiricism to 'contain risk' and perceive outliers of volatility, through probability.
Much like time, the validation of a mobile mean propagates that markets, or the actions
of participants will follow the mean itself. However, within markets, mean follows
price (and the larger shift of distributions), which can only surface when outliers of
traditional probably fail.
The author challenges whether it is truly probability that fails at these extreme
points within distributions, or rather, whether the greater perception and
implementation of probability, which is/was perhaps, flawed from the start?
The Never-Ending Search behind
Probability Distributions
Probability theory is generally thought of as the identification and measurement of
events within random phenomena, in an effort to unveil statistical patterns and
transparency within the seemingly arbitrary occurrences at hand.
It is important to understand that markets transcend rational probability analysis of
'games of chance', as the underlying fundamental events are really not 'random'
whatsoever.
As Jaume Masoliver, Miquel Montero and Josep M Porra stated in the December
1999 paper A Dynamical Model Describing Stock Market Price Distributions,
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"One of the most important problems in mathematical finance is to know the probability
distribution of speculative prices."53
The authors explain traditional Gaussian measurements often fail in markets as,
"Gaussian models are thus widely used in finance although as Kendall first noticed, the normal
distribution does not fit financial data especially at the wings of the distribution."
The aforementioned authors hit the nail on the head, in that traditional
implementation of a Gaussian distribution within financial markets fails to consider the
extensive volatility produced outliers that commonly surface.
Moreover, within the Central Limit Theorem, Wall Street has historically made the
mistake of assuming a finite mean and variance, which repeatedly falls victim to
unanticipated risk, losses and default as the distribution at hand slides away from the
preconceived outliers of normal probability.
The issue at hand within traditional analysis of probability and volatility is simply
the continued attempt to measure finite variance in an effort to locate mean and
outliers of probably.
Even when attempting to apply multi-dimensional alternatives like a multivariate
Gaussian distribution, or matrix normal distribution, markets seemingly incorrectly
assume price action is linear, or in effect: not.
The same problem is again encountered in the previously mentioned models, in that
when one attempts to identify the variance in distributions at all, the conclusion is a
failed measurement of deviations from normality.
Within this line of thought, the same problem arises repeatedly…that regardless of
man's attempt at identifying probability and volatility within any given distribution,
the grave mistake of assuming a finite variance has been, or is to be, made.
Referencing the paper from Masoliver, Montero and Porra again; the authors
conclude, "Summarizing by means of a continuous description of random pulses, we have
obtained a dynamical model leading to a probability distribution for the speculative price
changes."
To rephrase, there is substantial brilliance within Masoliver, Montero and Porra's
modeling; when considering a larger failure of understanding is taking place within
most statistical thinking (regarding markets) whenever considering markets are static,
or that distributions are not constantly in motion…
Continuing our discussion of the historical study of price distributions and
probability, it can be said that the larger goal of most eco-physics statisticians has
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historically attempted to identify potential tails for prices and returns within
distributions.
Case in point, quoting the paper Stock Market Return Distributions: From Past to
Present submitted to the Institute of Nuclear Physics, Polish Academy of Science in
2007 by S. Drożdż, M. Forczek, J. Kwapień, P. Oświe¸cimka and R. Rak, "Much effort has
been devoted on both the empirical and the theoretical level to such phenomena like fat-tailed
distributions of financial fluctuations, persistent correlations in volatility, multi-fractal
properties of returns etc. Specifically, the interest in the return distributions can be traced back
to an early work of Mandelbrot, in which he proposed a Levy process as the one governing the
logarithmic price fluctuations."
The authors continue with, "This empirical property of price and index returns led to the
formulation of the so-called inverse cubic power law, which was soon followed by an attempt of
formulating its theoretical foundation. Subsequent related study revealed that, opposite to the
earlier outcomes of, the tail shape of the return distributions might no longer be so stable along
time axis."
The aforementioned study of price action examined American Stock Market
companies from 1994-1995 and 1998-99, but then extended to examine 1000 of the
largest American companies. The authors concluded, "The difference of the results for the
same market but for different time intervals might suggest that the scaling behavior is not stable
and depends on some crucial factors as, for example, the speed of information processing which
constantly increases from past to present."
Despite all of the incredible breakthroughs in financial modeling over the years, it
may be possible one aspect of 'modeling' statisticians have missed is one of simplicity,
in that prices, given the continual urge of men to profit, will never remain stagnate and
thus, with each passing day, present a new 'paradigm' of subset distribution
movement. Thus, perhaps true understanding to movements within markets (past,
present and future) simply because, as is the nature of man, overcomplicating matters
seemingly creates validity, especially if the true answer is/was in plain sight from the
start. In reality, the answer to many of market's failed risk modeling is not in the larger
consideration of the macro picture, but in the oversight of the power within smaller
subset distribution movement.
To shed a slight bit more light on this understanding, the author would like to
politely request the reader to keep an open mind to a potentially larger paradigm shift
in the preconceived understanding of probability/ volatility and distributions, as a
measurement of tails, risk and returns. Instead, our greater understanding of dynamics
behind the movement of subset distributions altogether may just very well be the key
unlocking answers to all of the above.
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Chinese Restaurant Process,
Probability/ Volatility and
Distributions
To find a greater understanding of market movement's we must keep Levy
processes in mind; however, the true answer within probably, volatility and
distributions may actually be found in the evolution of techniques used to derive
machine learning.
As a brief definition, machine learning is the intersection of computer science and
statistics. Computer science is the measurement of data and statistics apply
probability. Ironically, while many academic institutions and Wall Street quant teams
have long-since focused on Levy-based models, the actual answers to currency market
movements may actually be within machine learning, whereby we are able to identify
clusters of market data and then make good decisions with poor and uncertain (noisy)
data.
The evolution may have come about as traditional Levy models have assisted in the
pricing of risk, the same models perhaps failed in predicting the larger movements of
distributions (and markets) overall.
Historically, with the implementation of statistics in markets, quantitative analysts
have assumed pricing data within markets as random variables with real vectors.
However, within the framework of the theory presented here, price action within
markets is actually comprised of complex data structures requiring more evolved
methods of measurement and inference.
Nonparametric Bayesian Methods eloquently help us see why this progression in
thought is necessary. Within Nonparametric Bayesian Methods, as price data surfaces,
we begin to see 'clusters', which statisticians historically have used in an attempt to
'break out' Gaussian models.
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The unknowns within cluster centers are known as theta, while the size of each
cluster, is better known as π.
Cluster centers
θ∈R^2d
Whereby we attempt to locate theta within the script, assuming the data is twodimensional.
Cluster proportions
π∈R^d
Thus, we attempt to locate theta within the script, assuming the data is twodimensional.
X_(i ~) N(θ_(j,) σ^2 I )
With probability π_i
P(θ,π )prior
By using Nonparametric Bayesian Methods the outcome is similar to Bayesian
inference, but with an infinite amount of parameters. The overall goal is to use the
clusters to dissolve the larger model, which in terms of price data, can be inferred as
the geometric presence of a one-dimensional chart.
Stock market data is similar to stick data and can be measured via Dirichlet Process,
thus creating a 'picket fence', or random probability distribution summing to 1. As the
data grows, the coherence of the probabilistic model also continues to gain momentum,
as much like protein folding and density estimations, we are able to move beyond the
historical attempt to measure risk and valuation.
Rather, we may instead be able to locate order flow and volatility transparency
through subset distributions (clusters of price data), seeking out angles of movement
through density of order flow, potentially surfacing within currency markets.
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In essence, when we begin to transcend the thought process that price data is flat,
we can begin to measure the total mass of clusters and thus, the density and angles of
potential movements at hand.
At the end of the day, when one is able to perceive 'density' within markets ahead of
the game, the larger paradigm of risk modeling quickly changes, all at the same time.
Before beginning the larger discussion of Beta Processes, we will first quickly cover
the Poisson Process and Levy Process. The Poisson Process allows us to identify
random points falling into an interval, thus deriving intensity and density within a
distribution.
We must find the "measure" within the Poisson Process, which gives the 'mass' to a
set, thus providing density within the data set.
Probability Density
Function (PDF)
Much like the decay of atoms holds a significantly large number of possible events,
each being rare, so does the larger set of outcomes within any given period of price
action within markets.
With a greater understanding of the Poisson Process, we are able to derive even
more information from the Levy Process, whereby we derive stochastic time series, or
random processes.
As information evolves, we will break out Brownian motion, thus invoking the
Langevin equation as well.
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Before moving too quickly (circling back to Levy Process) one might think of market
action much like atomic structure, in a discrete distribution, when we measure mass of
price data unfolding in markets, we find independent conclusions, with the data sets as
disjoint.
Thus, the Levy measure allows us to locate mass over omega Ω, which in the case of
currency markets, would be time. The Levy measure becomes the base measure of the
Poisson Process, whereby mass is the weight of data in time intervals. Because two
prints within markets cannot occur at the same moment in time, and must fall into a
time sequence, we are able to rationally justify this thought process.
The Levy Measure then helps calculate the mass on omega, deriving intensity,
whereby be arrive at the Beta Process, while pulling in the concept of Brownian motion
all at the same time, and in essence, creating a type of superprocess.
To back up for a moment, the Levy process (holding the Levy measure within a
Poisson Process) allows for inference of a random discrete measure presenting mass to
disjoint sets. However, much like atoms are not fixed, neither are markets.
With the aforementioned in mind, we will find some clues within the Beta Process,
whereby we discover similarities of market movements, volatility/probability and
pricing with that of atomic structure. Similarly, as Brownian motion gave birth to
Particle Theory, and continuous-time stochastic processes, Beta Processes hold that the
data within a distribution can be continuous, discreet, and mixed. The initial inferences
derive that all values can only sum 1, with all points presented as real numbers.
Bernoulli Sampling allows us to break out individual distributions within the larger
infinite time scale, thus bringing us to "Indian Buffet Process." Within the Indian Buffet
Process (Chinese Restaurant Process), one can think of the market as a large restaurant,
where customers step in to try an infinite amount of dishes, whereby each customer
can try a dish on the buffet line, at random. When a customer tries a dish (buys a
currency) his likelihood of trying that dish is equal to the probability of those who have
previously tried the same dish, which is the partial explanation for momentum within
markets, when breakouts and breakdowns occur. However, when ranges move, the
process invokes the Poisson Process whereby "new dishes" (market ranges) are
introduces as clusters of data within the larger time series of trading.
Moreover, because trading is an active process, whereby one can buy, as quickly as
he, or she may sell, we also invoke "exchangeability" within the larger concepts of
measuring density and intensity within the cluster movements (known as the
"hierarchies of Beta Processes.)
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As a quick, though loose example, assuming we have two days of market data,
measured in clusters, or distributions, we are able to infer the first of the two days as
our base measure of data. The second day allows that trades can take place at the same
data points; much like the motion of atoms. Because the data sets are disjoint, our goal
is to create an inferential algorithm for the clusters that have been created within the
market. In other words, by quantifying subset distributions, we are able to create
probability modeling for movement within markets, major pivot points within ranges,
and potential intensity of breakouts and breakdowns…when the distributions shift.
While market data is not truly a "nested clustering problem" as known in the
Dirichlet Process, the conceptual framework behind the data sets remains the same.
However, by categorizing hierarchies of clusters, we are able to create 'classes' of
probable movements and outcomes potentially about to unfold.
At this point, we find ourselves at the measurement of variance an Integer
Attributable Models, or our Inference Algorithms of market movement. Using Levy
Measures, the author concludes that we may be able to find rare occurrences of data
within the cluster data sets, which derive probability of, and into, movement.
Accordingly, we evolve our Levy Process thinking to Gamma Processes, whereby
we are able to begin seeking 'jump probability.'
In 2004, David Applebaum wrote that the gamma process can be written as Γ(t;γ,λ),
it is a pure-jump increasing Levy process with intensity measure ν(x) = γx − 1exp( −
λx), for positive x.
Because the Gamma Process may be measured in terms of the mean (μ) and
variance (v) per unit time, we find market action unfolding as:
γ = μ2 / v and λ = μ / v.
Conceptually, while we would like to measure the movement of the mean, the
author's recent research is instead focuses on the rarity of data clusters, and or
possibility of standard deviations actually surfacing not as larger points of regression,
but instead, the precise points where ranges shift, or 'jump.'
Within currency markets, by measuring the clusters in terms of omega (time) in
terms of each market as linear, we may derive that density both implies probable
intensity of jump and capacity of range 'locking' at the same time.
To date, the author has spent considerable time with a team in China creating code
to locate the clusters of data, which is now complete. We are now applying jumpprobability via the Beta process, while also seeking to attempt to find volatility and
probability of movement, or not, within the cluster subsets of market action.
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All of the aforementioned (again) serves as a hopeful 'jump point' to open further
discussion of the movement of subset distributions within financial markets, as one of
the larger clues to the seemingly random prices surfacing day-after-day and year-afteryear.
In the end, the larger principals behind Volatility Illuminated and the possibilities
of…reside more in challenging traditional paradigms, with the hope retail traders will
begin thinking of price action more in terms of physics and quantitative-statistics, over
historical methods of mere 'technicals-based' buying and selling.
One would think that as all things in this universe hold energy and matter, price
action, if even seen as a derivative of human emotion, would hold some of the same
attributes.
With all that I have mentioned, I would like to politely challenge readers to reshape
conventional views on market and trading action from that of 'the old standards' of
technical and fundamental analysis, to 'the new standard' of the expansion and
compression of energy as seen through volatility, probability and the movement of
subset distributions.
Finally – thank you so much for your time and support!
Mark Whistler
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Rules of
TRADING DISCIPLINE
1. NEVER OVER-LEVERAGE
2. Know the Economics.
Do not place a trade if you don't understand why the trade is being made.
3. NEVER EVER leave a position unattended without some sort of stop in place.
4. NEVER OVER-LEVERAGE
You will compromise your account by taking on a position that is too large to think
clearly.
5. When in Doubt Get Out.
If you can't sleep at night, get out of the trade.
Trust your instincts.
6. Missed Money is Better than Lost Money.
If you have a negative gut feeling about a trade
setup, stay out. There will always be opportunity to make money, but not if you don't
have any.
7. Send the Trade Away, Live to Trade Another Day. If it doesn't look, or feel right, get
out.
8. The First Loss is Always the Smallest Loss.
It's hard to take a loss, I know, I've taken plenty of them. I can tell you firsthand, you
will save a ton of money by taking the first loss, at your predetermined stop, rather
than letting your emotions keep you in a position.
Stop losses are a critical rule of money management.
9. Little Loss… Little Loss… HUGE WIN.
We must understand that there will be losses in trading.
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We will accept small losses, even if there are a string of them, knowing that a big win is
on the way.
We will never take a large loss by violating out stops, because doing so, would void the
trading plan we are working so hard to execute.
If you think small, you will get small.
Traders who constantly take little winners off the table eventually blow up.
10. Lazy is Crazy.
At every turn, we will work hard to improve our trading knowledge by reading and
studying everything we can.
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Six CORE PRINCIPLES
OF TECHNICAL ANALYSIS
Charting, like all technical analysis, must be understood for what it is. The core
principals to understanding what technical analysis is and why it is important are:
1. Charting and technical analysis are lagging indicators, meaning that they display
information about an event that has already occurred.
2. Using technical analysis alone, without regard to fundamentals, or news…is lazy,
and will often cause losses.
3. Technical analysis should be used as a "beacon in the night", signaling that an event,
or shift (fundamental, or news-oriented) within the market, or stock has occurred.
4. Often, technical analysis relies on 'self fulfilling prophecies', meaning that many
people must be watching, believe in, and act on the same data for signals to become
accurate.
5. There is no 'secret code' to markets. Some technical signals work better than others
do, but none will work "all of the time."
6.
Traders who utilize technical analysis (while also paying attention to
fundamentals and news too), but fail to remember simple 'common sense', will
eventually get killed.
A deep understanding of the above principals is vital to trading with technical
analysis. One must understand technicals for what they are, while keeping a clear head
as signals come about on a day-to-day basis.
In the end, common sense is king.
Mark Whistler
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Additional DISCLAIMER
Mark Whistler, fxVolatility, WallStreetRockStar.com and 2034thecorporation.com
("Company") is not an investment advisory service, nor a registered investment advisor
or broker-dealer and does not purport to tell or suggest which securities or currencies
customers should buy or sell for themselves. The analysts and employees or affiliates of
Company may hold positions in the stocks, currencies or industries discussed here.
You understand and acknowledge that there is a very high degree of risk involved in
trading securities and/or currencies. The Company, the authors, the publisher, and all
affiliates of Company assume no responsibility or liability for your trading and
investment results. Factual statements on the Company's website, or in its publications,
are made as of the date stated and are subject to change without notice.
It should not be assumed that the methods, techniques, or indicators presented in
these products will be profitable or that they will not result in losses. Past results of any
individual trader or trading system published by Company are not indicative of future
returns by that trader or system, and are not indicative of future returns which be
realized by you. In addition, the indicators, strategies, columns, articles and all other
features of Company's products (collectively, the "Information") are provided for
informational and educational purposes only and should not be construed as
investment advice. Examples presented on Company's website are for educational
purposes only. Such set-ups are not solicitations of any order to buy or sell.
Accordingly, you should not rely solely on the Information in making any investment.
Rather, you should use the Information only as a starting point for doing additional
independent research in order to allow you to form your own opinion regarding
investments. You should always check with your licensed financial advisor and tax
advisor to determine the suitability of any investment.
Mark Whistler
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Page 275 of 308
Custom Indicator Code
I
WAVE ● PM
Copyright © Mark Whistler 2009 / fxVolatility.com.
//+--------------------------------------------------+
//|Whistler Active Volatility Energy - Price Mass
|
//| Price Mass WAVE-PM
|
//| Copyright 2009, fxVolatility.com
|
//| Authors: Mark Whistler/EcTrader.net
|
//| Mark@WallStreetRockStar.com
|
//|www.WallStreetRockStar.com|www.fxVolatility.com. |
//+--------------------------------------------------+
#property copyright "Copyright 2009, Mark Whistler"
#property link "http://www.wallstreetrockstar.com"
#property
#property
#property
#property
#property
#property
indicator_separate_window
indicator_buffers 6
indicator_maximum 1
indicator_minimum 0
indicator_color5 Blue
indicator_color6 Red
//---- indicator parameters
extern int
ShortBandsPeriod=14;
extern int
ShortBandsShift=0;
extern double ShortBandsDeviations=2.2;
extern int
LongBandsPeriod=55;
extern int
LongBandsShift=0;
extern double LongBandsDeviations=2.2;
extern int PERIODS_CHARACTERISTIC=100;
//---- buffers
double ShortMovingBuffer[];
double LongMovingBuffer[];
double ShortDev[];
double LongDev[];
double Shortoscillator[];
double Longoscillator[];
//+---------------------------------------------------+
//| Custom indicator initialization function
|
//+---------------------------------------------------+
int init()
{
//---- indicators
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SetIndexStyle(0,DRAW_NONE);
SetIndexBuffer(0,ShortMovingBuffer);
SetIndexStyle(1,DRAW_NONE);
SetIndexBuffer(1,LongMovingBuffer);
SetIndexStyle(2,DRAW_NONE);
SetIndexBuffer(2,ShortDev);
SetIndexStyle(3,DRAW_NONE);
SetIndexBuffer(3,LongDev);
SetIndexStyle(4,DRAW_LINE);
SetIndexBuffer(4,Shortoscillator);
SetIndexStyle(5,DRAW_LINE);
SetIndexBuffer(5,Longoscillator);
//---SetIndexDrawBegin(0,ShortBandsPeriod+ShortBandsShift);
SetIndexDrawBegin(1,LongBandsPeriod+LongBandsShift);
SetIndexDrawBegin(2,ShortBandsPeriod+ShortBandsShift);
SetIndexDrawBegin(3,LongBandsPeriod+LongBandsShift);
SetIndexDrawBegin(4,ShortBandsPeriod+ShortBandsShift);
SetIndexDrawBegin(5,LongBandsPeriod+LongBandsShift);
//---return(0);
}
//+---------------------------------------------------+
//| Bollinger Bands
|
//+---------------------------------------------------+
int start()
{
int
i,k,counted_bars=IndicatorCounted();
double deviation;
double sum,oldval,newres;
//---if(Bars<=LongBandsPeriod) return(0);
//---- initial zero
if(counted_bars<1)
{
for(i=1;i<=ShortBandsPeriod;i++)
{
ShortMovingBuffer[Bars-i]=EMPTY_VALUE;
}
for(i=1;i<=LongBandsPeriod;i++)
{
LongMovingBuffer[Bars-i]=EMPTY_VALUE;
}
}
//---int limit=Bars-counted_bars;
if(counted_bars>0) limit++;
for(i=0; i<limit; i++)
{
ShortMovingBuffer[i]=iMA(NULL,0,ShortBandsPeriod,ShortBandsShift,MODE_SMA,PRICE_CLOSE,i);
LongMovingBuffer[i]=iMA(NULL,0,LongBandsPeriod,LongBandsShift,MODE_SMA,PRICE_CLOSE,i);
}
//---i=Bars-ShortBandsPeriod+1;
if(counted_bars>ShortBandsPeriod-1) i=Bars-counted_bars-1;
while(i>=0)
{
sum=0.0;
k=i+ShortBandsPeriod-1;
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oldval=ShortMovingBuffer[i];
while(k>=i)
{
newres=Close[k]-oldval;
sum+=newres*newres;
k--;
}
ShortDev[i]=ShortBandsDeviations*MathSqrt(sum/ShortBandsPeriod);
Shortoscillator[i]=OscillatorLine(ShortDev,i);
//UpperBuffer[i]=oldval+deviation;
//LowerBuffer[i]=oldval-deviation;
i--;
}
//---i=Bars-LongBandsPeriod+1;
if(counted_bars>LongBandsPeriod-1) i=Bars-counted_bars-1;
while(i>=0)
{
sum=0.0;
k=i+LongBandsPeriod-1;
oldval=LongMovingBuffer[i];
while(k>=i)
{
newres=Close[k]-oldval;
sum+=newres*newres;
k--;
}
LongDev[i]=LongBandsDeviations*MathSqrt(sum/LongBandsPeriod);
Longoscillator[i]=OscillatorLine(LongDev,i);
//UpperBuffer[i]=oldval+deviation;
//LowerBuffer[i]=oldval-deviation;
i--;
}
//---return(0);
}
double OscillatorLine(double indicator[], int StartBar)
{
double S=0;
int ArrayLong=PERIODS_CHARACTERISTIC;
double Result;
for(int j=StartBar;j<ArrayLong+StartBar;j++)
{S+=MathPow((indicator[j]/Point),2);}
S/=ArrayLong;
S=MathSqrt(S)*Point;
if(S!=0)
{Result=indicator[StartBar]/S;}
Result=MathTanh(Result);
return (Result);
}
double MathTanh(double x)
{
double exp;
double returnNum;
if(x>0)
{
exp=MathExp(-2*x);
returnNum= (1-exp)/(1+exp);
return (returnNum);
}
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else
{
}
}
exp=MathExp(2*x);
returnNum=(exp-1)/(1+exp);
return (returnNum);
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Custom Indicator Code
II
Duel CCI with Signal
Copyright © Mark Whistler 2009 / fxVolatility.com.
//+--------------------------------------------------+
//| Duel CCI w/Signal
|
//| Copyright 2009, fxVolatility.com
|
//| Authors: Mark Whistler/EcTrader.net
|
//| Mark@WallStreetRockStar.com
|
//|www.WallStreetRockStar.com|www.fxVolatility.com. |
//+--------------------------------------------------+
#property copyright "Copyright 2009, Mark Whistler"
#property link "http://www.wallstreetrockstar.com"
#property indicator_separate_window
#property indicator_buffers 4
#property indicator_color1 SteelBlue
#property indicator_color2 Red
#property indicator_color3 OrangeRed
#property indicator_width3 2
#property indicator_color4 MediumSpringGreen
#property indicator_width4 2
//---- input parameters
extern int CCIPeriod1 = 14;
extern int CCIPeriod2 = 100;
extern int Num_CountBarOf220To64=10000;
extern int Num_Bigger=220;
extern int Num_Smaller=64;
int count;
//---- buffers
double CCIBuffer1[];
double CCIBuffer2[];
double CCIArrow1[];
double CCIArrow2[];
//+---------------------------------------------------+
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//| Begin Custom Indicator
|
//+---------------------------------------------------+
int deinit()
{
//ObjectsDeleteAll();
return(0);
}
int init()
{
string short_name;
//---- indicator line
SetIndexStyle(0, DRAW_LINE, STYLE_SOLID, 1, SteelBlue);
SetIndexStyle(1, DRAW_LINE);
SetIndexStyle(2,DRAW_ARROW);
SetIndexStyle(3,DRAW_ARROW);
SetIndexBuffer(0, CCIBuffer1);
SetIndexBuffer(1, CCIBuffer2);
SetIndexBuffer(2, CCIArrow1);
SetIndexBuffer(3, CCIArrow2);
SetIndexArrow(2,234);
SetIndexArrow(3,233);
//---- name for DataWindow and indicator subwindow label
short_name = "CCIW(" + CCIPeriod1 + ", " + CCIPeriod2 + ")";
IndicatorShortName(short_name);
SetIndexLabel(0, "CCIW(" + CCIPeriod1 + ")");
SetIndexLabel(1, "CCIW(" + CCIPeriod2 + ")");
SetIndexLabel(2, "CCIW(" + "CCIArrow1" + ")");
SetIndexLabel(3, "CCIW(" + "CCIArrow2" + ")");
//---SetIndexDrawBegin(0, CCIPeriod1);
SetIndexDrawBegin(1, CCIPeriod2);
SetIndexDrawBegin(2, CCIArrow1);
SetIndexDrawBegin(3, CCIArrow2);
//---return(0);
}
//+---------------------------------------------------+
//| CCI
|
//+---------------------------------------------------+
int start()
{
int i, counted_bars = IndicatorCounted();
//---if(Bars <= CCIPeriod1)
return(0);
//---- initial zero
if(counted_bars < 1)
for(i = 1; i <= CCIPeriod1; i++)
CCIBuffer1[Bars-i] = 0.0;
//---i = Bars - CCIPeriod1 - 1;
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if(counted_bars >= CCIPeriod1)
i = Bars - counted_bars - 1;
bool success1=false;
bool success2=false;
int j=1;
while(i >= 0)
{
CCIBuffer1[i] = iCCI(NULL, 0, CCIPeriod1, PRICE_TYPICAL, i);
CCIBuffer2[i] = iCCI(NULL, 0, CCIPeriod2, PRICE_TYPICAL, i);
if (CCIBuffer2[i]<=Num_Smaller &&
CCIBuffer2[i+1]>=Num_Smaller)
{
for (j=1; j<=Num_CountBarOf220To64; j++)
{
if (CCIBuffer2[j+i]<Num_Smaller)
{
success1=false;
break;
}
if (CCIBuffer2[j+i]>=Num_Bigger)
{
success1=true;
break;
}
}//}
if (success1==true)
{
CCIArrow1[i]=CCIBuffer2[i];
count++;
success1=false;
}
else
{
CCIArrow1[i]=EMPTY_VALUE;
}
}
//----------------------------if (CCIBuffer2[i]>=(-1*Num_Smaller) && CCIBuffer2[i+1]<=(-1*Num_Smaller))
{
for (j=1; j<=Num_CountBarOf220To64; j++)
{
if (CCIBuffer2[j+i]>(-1*Num_Smaller))
{
success2=false;
break;
}
if (CCIBuffer2[j+i]<=(-1*Num_Bigger))
{
success2=true;
break;
}
}//}
if (success2==true)
{
CCIArrow2[i]=CCIBuffer2[i];
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}
else
{
}
}
}
success2=false;
CCIArrow2[i]=EMPTY_VALUE;
}
success1=false;
success2=false;
i--;
return(0);
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Custom Indicator Code
III
WVAV
Copyright © Mark Whistler 2009 / fxVolatility.com.
//+--------------------------------------------------+
//|Whistler Volume Adjusted Volatility - WVAV
|
//|
|
//| Copyright 2009, fxVolatility.com
|
//| Authors: Mark Whistler/EcTrader.net
|
//| Mark@WallStreetRockStar.com
|
//|www.WallStreetRockStar.com|www.fxVolatility.com. |
//+--------------------------------------------------+
#property copyright "Copyright 2009, Mark Whistler"
#property link "http://www.wallstreetrockstar.com"
//---#property
#property
#property
#property
#property
indicator_chart_window
indicator_buffers 5
indicator_color1 Red
indicator_color2 DarkGoldenrod
indicator_color3 Black
#property indicator_color4 Black
#property indicator_color5 Black
//---extern
extern
extern
//---extern
//---extern
extern
extern
extern
input parameters
int MA_Ticks = 10000;
int MA_Shift = 0;
int MA_Start = 500;
indicator parameters1
string aa="*****************************";
indicator parameters
bool MidBandVisible=false;
int
BandsPeriod=14;
int
BandsShift=0;
double BandsDeviations=3.2;
//---- indicator buffers
double ExtMapBuffer[];
double ExpVolBuffer[];
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//---- buffers
//---- double MovingBuffer[];
double UpperBuffer[];
double LowerBuffer[];
//-------------//+---------------------------------------------------+
//|Custom Indicator Initialization
|
//+---------------------------------------------------+
int init()
{
//---SetIndexStyle(0, DRAW_LINE);
SetIndexShift(0, MA_Shift);
//---- indicator buffers mapping
SetIndexBuffer(0, ExtMapBuffer);
SetIndexStyle(1, DRAW_NONE);
SetIndexBuffer(1, ExpVolBuffer);
SetIndexDrawBegin(0, 0);
//---- initialization done
//---- indicators
SetIndexStyle(2,DRAW_LINE);
SetIndexBuffer(2,ExtMapBuffer);
SetIndexStyle(3,DRAW_LINE);
SetIndexBuffer(3,UpperBuffer);
SetIndexStyle(4,DRAW_LINE);
SetIndexBuffer(4,LowerBuffer);
//---SetIndexDrawBegin(2,BandsPeriod+BandsShift);
SetIndexDrawBegin(3,BandsPeriod+BandsShift);
SetIndexDrawBegin(4,BandsPeriod+BandsShift);
return(0);
}
//+---------------------------------------------------+
//|Custom Indicator Initialization
|
//+---------------------------------------------------+
int start()
{
int counted_bars = IndicatorCounted();
int rest = Bars - counted_bars;
int restt = Bars - counted_bars;
double sumVol;
int ts;
int evol;
int volsum;
int j;
int i;
//---------------Begin Add MA----------------------double deviation;
double sum, oldval,newres;
//---if(Bars<=BandsPeriod) return(0);
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//---- initial zero
if(counted_bars<1)
for(i=1;i<=BandsPeriod;i++)
{
ExtMapBuffer[Bars-i]=EMPTY_VALUE;
UpperBuffer[Bars-i]=EMPTY_VALUE;
LowerBuffer[Bars-i]=EMPTY_VALUE;
}
int limit=Bars-counted_bars;
if(counted_bars>0) limit++;
for(i=0; i<limit; i++)
{
ExtMapBuffer[i]=iMA(NULL,0,BandsPeriod,BandsShift,MODE_SMA,PRICE_CLOSE,i);
}
//---------------End Add MA----------------------//---------Begin Volume MA-------------------------while(restt >= 0)
{
volsum = 0;
for(int k = 0; k < 30; k++)
volsum += iVolume(NULL, 0, restt + k*24);
ExpVolBuffer[restt] = volsum / 30;
restt--;
}
//---while(ExpVolBuffer[rest] == 0 && rest >= 0)
rest--;
rest -= MA_Ticks / 200;
if(rest > MA_Start)
rest = MA_Start;
//---while(rest >= 0)
{
sumVol = 0;
ts = 0;
j = rest;
while(ts < MA_Ticks)
{
evol = ExpVolBuffer[j];
//---Print("Evol = ", evol);
if(ts + evol < MA_Ticks)
{
sumVol += evol * Open[j];
ts += evol;
}
else
{
sumVol += (MA_Ticks - ts) * Open[j];
ts = MA_Ticks;
}
j++;
}
ExtMapBuffer[rest] = sumVol / MA_Ticks;
rest--;
}
//----------------------End Volume MA----------------//---------------------Begin Bollinger Band-----------
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//---i=Bars-BandsPeriod+1;
if(counted_bars>BandsPeriod-1) i=Bars-counted_bars-1;
while(i>=0)
{
sum=0.0;
k=i+BandsPeriod-1;
oldval=ExtMapBuffer[i];
while(k>=i)
{
newres=Close[k]-oldval;
sum+=newres*newres;
k--;
}
deviation=BandsDeviations*MathSqrt(sum/BandsPeriod);
UpperBuffer[i]=oldval+deviation;
LowerBuffer[i]=oldval-deviation;
i--;
}
//---//-----------------------End Band--------------------//---return(0);
}
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Bibliography / Recommended
Reading
Recommended Reading: Statistics
• Best, Joel (2001). Damned Lies and Statistics: Untangling Numbers from the Media, Politicians,
and Activists. University of California Press. ISBN 0-520-21978-3.
• Desrosières, Alain (2004). The Politics of Large Numbers: A History of Statistical Reasoning.
Trans. Camille Naish. Harvard University Press. ISBN 0-674-68932-1.
• Hacking, Ian (1990). The Taming of Chance. Cambridge University Press. ISBN 0-521-38884-8.
• Lindley, D.V. (1985). Making Decisions (2nd ed. ed.). John Wiley & Sons. ISBN 0-471-90808-8.
• Tijms, Henk (2004). Understanding Probability: Chance Rules in Everyday life. Cambridge
University Press. ISBN 0-521-83329-9.
Recommended Reading: DotCom Bubble
• Cassidy, John. Dot.con: How America Lost its Mind and Its Money in the Internet Era (2002)
• Daisey, Mike. 21 Dog Years Free Press. ISBN 0-7432-2580-5.
• Goldfarb, Brent D., Kirsch, David and Miller, David A., "Was There Too Little Entry During the
Dot Com Era?" (April 24, 2006). Robert H. Smith School Research Paper No. RHS 06-029 Available
at SSRN: http://ssrn.com/abstract=899100
• Kindleberger, Charles P., Manias, Panics, and Crashes: A History of Financial Crises (Wiley, 2005,
5th edition)
• Kuo, David dot.bomb: My Days and Nights at an Internet Goliath ISBN 0-316-60005-9 (2001)
• Lowenstein, Roger. Origins of the Crash: The Great Bubble and Its Undoing. (Penguin Books,
2004) ISBN 0-14-303467-7
Recommended Reading: Algorithmic Trading
• MTS to mull bond access, The Wall Street Journal Europe, April 18, 2007, p. 21
• Sornette (2003): Critical Market Crashes, Sornette (2003): Critical Market Crashes
• Trading with the help of 'guerrillas' and 'snipers,' Financial Times, March 19, 2007
• Rob Curren, Watch Out for Sharks in Dark Pools, The Wall Street Journal, August 19, 2008, p. c5.
Available at WSJ Blogs
• Artificial intelligence applied heavily to picking stocks by Charles Duhigg, November 23, 2006
• Carney, John (June 26, 2009). "UBS Accuses Three Quant Traders Of Stealing Its Secret Code". The
Business Insider. http://www.businessinsider.com/ubs-accuses-three-quant-traders-of-stealingits-secret-code-2009-6. Retrieved on July 14, 2009.
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End Notes
1
Richard S. Newman, Transformation of American abolitionism: fighting slavery in the early Republic chapter 1
Results from the 1860 Census: The Civil War Home Page. Civil-War.net. Accessed: June 2009.
http://www.civil-war.net/about_us.asp
2
Remembering 1975 – The Majority was Wrong – The Good News Economist. December 11, 2008. Accessed
June, 2009.
3
http://mast-economy.blogspot.com/2008/12/remembering-1975-majority-was-wrong.html
Buffet, Warren. Buy American. I am. October 16, 2008. The New York Times.
http://www.nytimes.com/2008/10/17/opinion/17buffett.html
4
5
Loftus, Elizabeth F. Make-believe memories," American Psychologist (November 2003).
Cozens, Claire. Ads Can Alter Memory Claim Scientists. UK Guardian. September 4, 2001.
http://www.guardian.co.uk/media/2001/sep/04/advertising
6
7
"Make my Memory" in Psychology & Marketing (2002)
8
Stewart's Beverages - Then & Again!
http://www.drinkstewarts.com/history.aspx
Dot-com bubble. (2009, June 6). In Wikipedia, The Free Encyclopedia. Retrieved 23:16, June 6, 2009, from
http://en.wikipedia.org/w/index.php?title=Dot-com_bubble&oldid=294871219
9
Wolff, Michael Dot-Com Bomb. New York Magazine. Published Apr 24, 2000.
http://nymag.com/nymetro/news/media/columns/medialife/2978/
10
Connors, E., Lundregan, T., Miller, N. & McEwan, T. Convicted by Juries, Exonerated by Science:
Case Studies in the Use of DNA Evidence to Establish
11
Innocence After Trial (National Institute of Justice, Alexandria, Virginia, 1996).
Loftus, Elizabeth F. "Our changeable memories: legal and practical implications," in Nature Reviews:
Neuroscience (2003).
12
Loftus, Elizabeth F. "Memory Faults and Fixes" in Issues in Science & Technology (2002; publication of
the National Academies of Science)
http://faculty.washington.edu/eloftus/Articles/IssuesInScienceTechnology02%20vol%2018.pdf
13
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Loftus, Elizabeth F. "Memory Faults and Fixes" in Issues in Science & Technology (2002; publication of
the National Academies of Science)
http://faculty.washington.edu/eloftus/Articles/IssuesInScienceTechnology02%20vol%2018.pdf
14
Understanding Your Fears – Author uncited. John Wiley & Sons, 2003.
http://media.wiley.com/product_data/excerpt/28/04712727/0471272728.pdf Accessed: May 2009.
15
Injuries in Athletics: Causes and Consequences Slobounov, Semyon 2008, XV, 544 p. 39 illus., 4 in
color., Hardcover ISBN: 978-0-387-72576-5
16
Title 18, U.S.C., Section 241
Conspiracy Against Rights .S. Federal Government, U.S. Department of Justice.
17
http://www.fbi.gov/hq/cid/civilrights/statutes.htm#section241
Loftus, Elizabeth F. Make-believe memories," American Psychologist (November 2003). Accessed: May
2009.
18
Greg Sandoval Start-up with pricey Super Bowl ad goes bust
Staff Writer, CNET News June 14, 2000 2:00 PM PDT
http://news.cnet.com/2100-1017-241907.html
19
Loftus, Elizabeth F. Make-believe memories," American Psychologist (November 2003). Accessed: May
2009.
20
21
University of Michigan: Consumer Confidence: Philadelphia Fed
http://www.philadelphiafed.org/payment-cards-center/tools-for-researchers/datadictionary/Umich-CCon_4-11-04.pdf Accessed: May 2009.
22
ST311 Introduction to Statistics Steve Stanislav Lecture Notes Accessed: May 2009.
http://www4.ncsu.edu/~sjstanis/notes.pdf Accessed: May 2009.
Creative Research Systems: Sample Size Calculator. Accessed: May 2009.
http://www.surveysystem.com/sscalc.htm Accessed: May 2009.
23
An Overview of The Study of Economics Principles, Concepts & Applications - The Study of
Economics is a new concept in learning Economics. Accessed: May 2009.
24
The McGraw-Hill Companies. http://www.dushkin.com/connectext/econ/help.mhtml Accessed:
May 2009.
25
Assets and Liabilities of Commercial Banks in the United Seasonally adjusted
http://www.federalreserve.gov/releases/h8/Current/
Ecnonomy.com. U.S. Crisis Response. June, 2009.
http://www.economy.com/dismal/pro/data/us-financial-crisis-response.asp?edition=1
26
27
Max Planck The Nobel Prize in Physics 1918. The Official Web Site of the Nobel Foundation
http://nobelprize.org/nobel_prizes/physics/laureates/1918/planck-bio.html
Accessed: May 2009.
Mark Whistler
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Page 290 of 308
Gorard, Stephen. Revisiting a 90-year-old debate: the advantages of the mean deviation. Department
of Educational Studies, University of York. Paper presented at the British Educational Research
Association Annual Conference, University of Manchester, 16-18 September 2004. Accessed: May 2009.
http://www.leeds.ac.uk/educol/documents/00003759.htm
28
Elementary Statistics – by Mario F. Triola, Eighth Edition
THEOREMS
29
DEFININITIONS, RULES AND
How Stock Indices Work - WIKINVEST.com - Accessed: March 2009.
http://www.wikinvest.com/wiki/How_Stock_Indices_Work Accessed: May 2009.
30
New Dow Divisor for Dow Jones Industrial Average. June 9, 2009.
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"Moody's downgraded A.I.G.'s senior unsecured debt on Friday and said it might downgrade other
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business."
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is a normal distribution, the way things ought to be. The shorter hump is a distribution like the stock
market's, less small changes than one would expect and more large changes. The amount of difference
between the two humps is known as kurtosis and it is a significant quantity for stocks."
45
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karma
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